diff --git a/404.html b/404.html
index 4bc1993..73e4204 100644
--- a/404.html
+++ b/404.html
@@ -27,7 +27,7 @@
 
     <a class="navbar-brand me-2" href="https://darwin-eu.github.io/visOmopResults/index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -40,10 +40,11 @@
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
   <ul class="dropdown-menu" aria-labelledby="dropdown-articles">
-<li><a class="dropdown-item" href="https://darwin-eu.github.io/visOmopResults/articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="https://darwin-eu.github.io/visOmopResults/articles/tables.html">Formatting tables</a></li>
+<li><a class="dropdown-item" href="https://darwin-eu.github.io/visOmopResults/articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="https://darwin-eu.github.io/visOmopResults/articles/a02_plots.html">Plots</a></li>
   </ul>
 </li>
+<li class="nav-item"><a class="nav-link" href="https://darwin-eu.github.io/visOmopResults/news/index.html">Changelog</a></li>
       </ul>
 <ul class="navbar-nav">
 <li class="nav-item"><form class="form-inline" role="search">
diff --git a/LICENSE.html b/LICENSE.html
index 11f7fe2..8f18b79 100644
--- a/LICENSE.html
+++ b/LICENSE.html
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -18,9 +18,10 @@
       <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -32,7 +33,7 @@
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="logo.png" class="logo" alt=""><h1>Apache License</h1>
-      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/v0.5.1/LICENSE.md" class="external-link"><code>LICENSE.md</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/LICENSE.md" class="external-link"><code>LICENSE.md</code></a></small>
     </div>
 
 <div id="apache-license" class="section level1">
diff --git a/articles/a01_tables.html b/articles/a01_tables.html
new file mode 100644
index 0000000..69857c6
--- /dev/null
+++ b/articles/a01_tables.html
@@ -0,0 +1,4607 @@
+<!DOCTYPE html>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en">
+<head>
+<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
+<meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
+<title>Tables • visOmopResults</title>
+<!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
+<link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
+<link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png">
+<link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png">
+<link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png">
+<link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png">
+<script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
+<link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet">
+<script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet">
+<link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet">
+<script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Tables">
+</head>
+<body>
+    <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
+
+
+    <nav class="navbar navbar-expand-lg fixed-top bg-light" data-bs-theme="light" aria-label="Site navigation"><div class="container">
+
+    <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
+
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
+
+
+    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
+      <span class="navbar-toggler-icon"></span>
+    </button>
+
+    <div id="navbar" class="collapse navbar-collapse ms-3">
+      <ul class="navbar-nav me-auto">
+<li class="nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
+<li class="active nav-item dropdown">
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles">
+<li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
+  </ul>
+</li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul>
+<ul class="navbar-nav">
+<li class="nav-item"><form class="form-inline" role="search">
+ <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json">
+</form></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+      </ul>
+</div>
+
+
+  </div>
+</nav><div class="container template-article">
+
+
+
+<link href="a01_tables_files/tabwid-1.1.3/tabwid.css" rel="stylesheet">
+<script src="a01_tables_files/tabwid-1.1.3/tabwid.js"></script><div class="row">
+  <main id="main" class="col-md-9"><div class="page-header">
+      <img src="../logo.png" class="logo" alt=""><h1>Tables</h1>
+            
+      
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/vignettes/a01_tables.Rmd" class="external-link"><code>vignettes/a01_tables.Rmd</code></a></small>
+      <div class="d-none name"><code>a01_tables.Rmd</code></div>
+    </div>
+
+    
+    
+<div class="section level2">
+<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
+</h2>
+<p>The <strong>visOmopResults</strong> package provides user-friendly
+tools for creating well-formatted tables and plots that are
+publication-ready. In this vignette, we focus specifically on the table
+formatting functionalities. The package supports four table formats: <a href="https://cran.r-project.org/package=tibble" class="external-link"><code>&lt;tibble&gt;</code></a>,
+<a href="https://cran.r-project.org/package=gt" class="external-link"><code>&lt;gt&gt;</code></a>,
+<a href="https://cran.r-project.org/package=flextable" class="external-link"><code>&lt;flextable&gt;</code></a>,
+and <a href="https://CRAN.R-project.org/package=DT" class="external-link"><code>&lt;datatables&gt;</code></a>.
+While <code>&lt;tibble&gt;</code> is an <code>&lt;data.frame&gt;</code>
+R object, <code>&lt;gt&gt;</code> and <code>&lt;flextable&gt;</code> are
+designed to create publication-ready tables that can be exported to
+different formats (e.g., PNG, Word, PDF, HTML), and
+<code>&lt;datatables&gt;</code> display tables on HTML pages. These last
+three can be used in ShinyApps, RMarkdown, Quarto, and more.</p>
+<p>Although the primary aim of the package is to simplify the handling
+of the <code>&lt;summarised_result&gt;</code> class (see <a href="https://CRAN.R-project.org/package=omopgenerics" class="external-link">omopgenerics</a>
+for more details), its functionalities can be applied to any
+<code>&lt;data.frame&gt;</code> if certain requirements are met.</p>
+<div class="section level3">
+<h3 id="types-of-table-functions">Types of Table Functions<a class="anchor" aria-label="anchor" href="#types-of-table-functions"></a>
+</h3>
+<p>There are two main categories of table functions in the package:</p>
+<ul>
+<li><p><strong>Main Table Functions</strong>: Comprehensive functions
+like <code><a href="../reference/visOmopTable.html">visOmopTable()</a></code> and <code><a href="../reference/visTable.html">visTable()</a></code> allow users
+to fully format tables, including specifying headers, grouping columns,
+and customising styles.</p></li>
+<li><p><strong>Additional Table Formatting Functions</strong>: The
+<code>format</code> function set provides more granular control over
+specific table elements, enabling advanced customisation beyond the main
+functions.</p></li>
+</ul>
+<p>This vignette will guide you through the usage of these
+functions.</p>
+</div>
+</div>
+<div class="section level2">
+<h2 id="main-functions">Main Functions<a class="anchor" aria-label="anchor" href="#main-functions"></a>
+</h2>
+<p>These functions are built on top of the <code>format</code>
+functions, providing a quick and straightforward way to format
+tables.</p>
+<div class="section level3">
+<h3 id="vistable">visTable()<a class="anchor" aria-label="anchor" href="#vistable"></a>
+</h3>
+<p><code><a href="../reference/visTable.html">visTable()</a></code> is a flexible function designed to format any
+<code>&lt;data.frame&gt;</code>.</p>
+<p>Let’s demonstrate its usage with a dataset from the
+<code>palmerpenguins</code> package.</p>
+<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://darwin-eu.github.io/visOmopResults/">visOmopResults</a></span><span class="op">)</span></span>
+<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://allisonhorst.github.io/palmerpenguins/" class="external-link">palmerpenguins</a></span><span class="op">)</span></span>
+<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span>
+<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://tidyr.tidyverse.org" class="external-link">tidyr</a></span><span class="op">)</span></span>
+<span><span class="va">x</span> <span class="op">&lt;-</span> <span class="va">penguins</span> <span class="op">|&gt;</span> </span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="op">!</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html" class="external-link">is.na</a></span><span class="op">(</span><span class="va">sex</span><span class="op">)</span> <span class="op">&amp;</span> <span class="va">year</span> <span class="op">==</span> <span class="fl">2008</span><span class="op">)</span> <span class="op">|&gt;</span> </span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="op">!</span><span class="st">"body_mass_g"</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across</a></span><span class="op">(</span><span class="fu"><a href="https://tidyselect.r-lib.org/reference/starts_with.html" class="external-link">ends_with</a></span><span class="op">(</span><span class="st">"mm"</span><span class="op">)</span>, <span class="op">~</span><span class="fu"><a href="https://rdrr.io/r/base/mean.html" class="external-link">mean</a></span><span class="op">(</span><span class="va">.x</span><span class="op">)</span><span class="op">)</span>, .by <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"species"</span>, <span class="st">"island"</span>, <span class="st">"sex"</span><span class="op">)</span><span class="op">)</span></span>
+<span><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">x</span><span class="op">)</span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 6 × 6</span></span></span>
+<span><span class="co">#&gt;   species island    sex    bill_length_mm bill_depth_mm flipper_length_mm</span></span>
+<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>   <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>     <span style="color: #949494; font-style: italic;">&lt;fct&gt;</span>           <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span>             <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span></span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> Adelie  Biscoe    female           36.6          17.2              187.</span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> Adelie  Biscoe    male             40.8          19.0              193.</span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> Adelie  Torgersen female           36.6          17.4              190 </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> Adelie  Torgersen male             40.9          18.8              194.</span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">5</span> Adelie  Dream     female           36.3          17.8              189 </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">6</span> Adelie  Dream     male             40.1          18.9              195</span></span></code></pre></div>
+<p>We can format this data into a <code>&lt;gt&gt;</code> table using
+<code><a href="../reference/visTable.html">visTable()</a></code> as follows:</p>
+<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="fu"><a href="../reference/visTable.html">visTable</a></span><span class="op">(</span></span>
+<span>  result <span class="op">=</span> <span class="va">x</span>,</span>
+<span>  groupColumn <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"sex"</span><span class="op">)</span>,</span>
+<span>  rename <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Bill length (mm)"</span> <span class="op">=</span> <span class="st">"bill_length_mm"</span>,</span>
+<span>             <span class="st">"Bill depth (mm)"</span> <span class="op">=</span> <span class="st">"bill_depth_mm"</span>,</span>
+<span>             <span class="st">"Flipper length (mm)"</span> <span class="op">=</span> <span class="st">"flipper_length_mm"</span>,</span>
+<span>             <span class="st">"Body mass (g)"</span> <span class="op">=</span> <span class="st">"body_mass_g"</span><span class="op">)</span>,</span>
+<span>  type <span class="op">=</span> <span class="st">"gt"</span>,</span>
+<span>  hide <span class="op">=</span> <span class="st">"year"</span></span>
+<span><span class="op">)</span></span></code></pre></div>
+<div id="mwlefoodfi" style="padding-left:0px;padding-right:0px;padding-top:10px;padding-bottom:10px;overflow-x:auto;overflow-y:auto;width:auto;height:auto;">
+<style>#mwlefoodfi table {
+  font-family: system-ui, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol', 'Noto Color Emoji';
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+}
+
+#mwlefoodfi thead, #mwlefoodfi tbody, #mwlefoodfi tfoot, #mwlefoodfi tr, #mwlefoodfi td, #mwlefoodfi th {
+  border-style: none;
+}
+
+#mwlefoodfi p {
+  margin: 0;
+  padding: 0;
+}
+
+#mwlefoodfi .gt_table {
+  display: table;
+  border-collapse: collapse;
+  line-height: normal;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  font-weight: normal;
+  font-style: normal;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#mwlefoodfi .gt_caption {
+  padding-top: 4px;
+  padding-bottom: 4px;
+}
+
+#mwlefoodfi .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#mwlefoodfi .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 3px;
+  padding-bottom: 5px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#mwlefoodfi .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#mwlefoodfi .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#mwlefoodfi .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#mwlefoodfi .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#mwlefoodfi .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#mwlefoodfi .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#mwlefoodfi .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#mwlefoodfi .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 5px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#mwlefoodfi .gt_spanner_row {
+  border-bottom-style: hidden;
+}
+
+#mwlefoodfi .gt_group_heading {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  text-align: left;
+}
+
+#mwlefoodfi .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#mwlefoodfi .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#mwlefoodfi .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#mwlefoodfi .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#mwlefoodfi .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#mwlefoodfi .gt_stub_row_group {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 5px;
+  padding-right: 5px;
+  vertical-align: top;
+}
+
+#mwlefoodfi .gt_row_group_first td {
+  border-top-width: 2px;
+}
+
+#mwlefoodfi .gt_row_group_first th {
+  border-top-width: 2px;
+}
+
+#mwlefoodfi .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#mwlefoodfi .gt_first_summary_row {
+  border-top-style: solid;
+  border-top-color: #D3D3D3;
+}
+
+#mwlefoodfi .gt_first_summary_row.thick {
+  border-top-width: 2px;
+}
+
+#mwlefoodfi .gt_last_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#mwlefoodfi .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#mwlefoodfi .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#mwlefoodfi .gt_last_grand_summary_row_top {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-bottom-style: double;
+  border-bottom-width: 6px;
+  border-bottom-color: #D3D3D3;
+}
+
+#mwlefoodfi .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#mwlefoodfi .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#mwlefoodfi .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#mwlefoodfi .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#mwlefoodfi .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#mwlefoodfi .gt_sourcenote {
+  font-size: 90%;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#mwlefoodfi .gt_left {
+  text-align: left;
+}
+
+#mwlefoodfi .gt_center {
+  text-align: center;
+}
+
+#mwlefoodfi .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#mwlefoodfi .gt_font_normal {
+  font-weight: normal;
+}
+
+#mwlefoodfi .gt_font_bold {
+  font-weight: bold;
+}
+
+#mwlefoodfi .gt_font_italic {
+  font-style: italic;
+}
+
+#mwlefoodfi .gt_super {
+  font-size: 65%;
+}
+
+#mwlefoodfi .gt_footnote_marks {
+  font-size: 75%;
+  vertical-align: 0.4em;
+  position: initial;
+}
+
+#mwlefoodfi .gt_asterisk {
+  font-size: 100%;
+  vertical-align: 0;
+}
+
+#mwlefoodfi .gt_indent_1 {
+  text-indent: 5px;
+}
+
+#mwlefoodfi .gt_indent_2 {
+  text-indent: 10px;
+}
+
+#mwlefoodfi .gt_indent_3 {
+  text-indent: 15px;
+}
+
+#mwlefoodfi .gt_indent_4 {
+  text-indent: 20px;
+}
+
+#mwlefoodfi .gt_indent_5 {
+  text-indent: 25px;
+}
+
+#mwlefoodfi .katex-display {
+  display: inline-flex !important;
+  margin-bottom: 0.75em !important;
+}
+
+#mwlefoodfi div.Reactable > div.rt-table > div.rt-thead > div.rt-tr.rt-tr-group-header > div.rt-th-group:after {
+  height: 0px !important;
+}
+</style>
+<table class="table gt_table" data-quarto-disable-processing="false" data-quarto-bootstrap="false">
+<thead><tr class="gt_col_headings">
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1" style="text-align: center; font-weight: bold;" scope="col" id="Species">Species</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1" style="text-align: center; font-weight: bold;" scope="col" id="Island">Island</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1" style="text-align: center; font-weight: bold;" scope="col" id="Bill-length-(mm)">Bill length (mm)</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1" style="text-align: center; font-weight: bold;" scope="col" id="Bill-depth-(mm)">Bill depth (mm)</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1" style="text-align: center; font-weight: bold;" scope="col" id="Flipper-length-(mm)">Flipper length (mm)</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<th colspan="5" class="gt_group_heading" style="background-color: #E9E9E9; font-weight: bold;" scope="colgroup" id="female">female</th>
+    </tr>
+<tr class="gt_row_group_first">
+<td headers="female  Species" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Adelie</td>
+<td headers="female  Island" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Biscoe</td>
+<td headers="female  Bill length (mm)" class="gt_row gt_right" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">36.6444444444444</td>
+<td headers="female  Bill depth (mm)" class="gt_row gt_right" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">17.2222222222222</td>
+<td headers="female  Flipper length (mm)" class="gt_row gt_right" style="text-align: left;">186.555555555556</td>
+</tr>
+<tr>
+<td headers="female  Species" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="female  Island" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Torgersen</td>
+<td headers="female  Bill length (mm)" class="gt_row gt_right" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">36.6125</td>
+<td headers="female  Bill depth (mm)" class="gt_row gt_right" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">17.4</td>
+<td headers="female  Flipper length (mm)" class="gt_row gt_right" style="text-align: left;">190</td>
+</tr>
+<tr>
+<td headers="female  Species" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="female  Island" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Dream</td>
+<td headers="female  Bill length (mm)" class="gt_row gt_right" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">36.275</td>
+<td headers="female  Bill depth (mm)" class="gt_row gt_right" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">17.7875</td>
+<td headers="female  Flipper length (mm)" class="gt_row gt_right" style="text-align: left;">189</td>
+</tr>
+<tr>
+<td headers="female  Species" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Gentoo</td>
+<td headers="female  Island" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Biscoe</td>
+<td headers="female  Bill length (mm)" class="gt_row gt_right" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">45.2954545454545</td>
+<td headers="female  Bill depth (mm)" class="gt_row gt_right" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">14.1318181818182</td>
+<td headers="female  Flipper length (mm)" class="gt_row gt_right" style="text-align: left;">213</td>
+</tr>
+<tr>
+<td headers="female  Species" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Chinstrap</td>
+<td headers="female  Island" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Dream</td>
+<td headers="female  Bill length (mm)" class="gt_row gt_right" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">46</td>
+<td headers="female  Bill depth (mm)" class="gt_row gt_right" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">17.3</td>
+<td headers="female  Flipper length (mm)" class="gt_row gt_right" style="text-align: left;">192.666666666667</td>
+</tr>
+<tr class="gt_group_heading_row">
+<th colspan="5" class="gt_group_heading" style="background-color: #E9E9E9; font-weight: bold;" scope="colgroup" id="male">male</th>
+    </tr>
+<tr class="gt_row_group_first">
+<td headers="male  Species" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Adelie</td>
+<td headers="male  Island" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Biscoe</td>
+<td headers="male  Bill length (mm)" class="gt_row gt_right" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">40.7555555555556</td>
+<td headers="male  Bill depth (mm)" class="gt_row gt_right" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">19.0333333333333</td>
+<td headers="male  Flipper length (mm)" class="gt_row gt_right" style="text-align: left;">192.555555555556</td>
+</tr>
+<tr>
+<td headers="male  Species" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="male  Island" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Torgersen</td>
+<td headers="male  Bill length (mm)" class="gt_row gt_right" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">40.925</td>
+<td headers="male  Bill depth (mm)" class="gt_row gt_right" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">18.8375</td>
+<td headers="male  Flipper length (mm)" class="gt_row gt_right" style="text-align: left;">193.5</td>
+</tr>
+<tr>
+<td headers="male  Species" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="male  Island" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Dream</td>
+<td headers="male  Bill length (mm)" class="gt_row gt_right" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">40.1125</td>
+<td headers="male  Bill depth (mm)" class="gt_row gt_right" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">18.8875</td>
+<td headers="male  Flipper length (mm)" class="gt_row gt_right" style="text-align: left;">195</td>
+</tr>
+<tr>
+<td headers="male  Species" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Gentoo</td>
+<td headers="male  Island" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Biscoe</td>
+<td headers="male  Bill length (mm)" class="gt_row gt_right" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">48.5391304347826</td>
+<td headers="male  Bill depth (mm)" class="gt_row gt_right" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">15.704347826087</td>
+<td headers="male  Flipper length (mm)" class="gt_row gt_right" style="text-align: left;">222.086956521739</td>
+</tr>
+<tr>
+<td headers="male  Species" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Chinstrap</td>
+<td headers="male  Island" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Dream</td>
+<td headers="male  Bill length (mm)" class="gt_row gt_right" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">51.4</td>
+<td headers="male  Bill depth (mm)" class="gt_row gt_right" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">19.6</td>
+<td headers="male  Flipper length (mm)" class="gt_row gt_right" style="text-align: left;">202.777777777778</td>
+</tr>
+</tbody>
+</table>
+</div>
+<p>To use the arguments <code>estimateName</code> and
+<code>header</code>, the <code>&lt;data.frame&gt;</code> must have the
+estimates arranged into three columns: <code>estimate_name</code>,
+<code>estimate_type</code>, and <code>estimate_value</code>. Let’s
+reshape the example dataset accordingly and demonstrate creating a
+<code>&lt;flextable&gt;</code> object:</p>
+<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="co"># Transforming the dataset to include estimate columns</span></span>
+<span><span class="va">x</span> <span class="op">&lt;-</span> <span class="va">x</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://tidyr.tidyverse.org/reference/pivot_longer.html" class="external-link">pivot_longer</a></span><span class="op">(</span></span>
+<span>    cols <span class="op">=</span> <span class="fu"><a href="https://tidyselect.r-lib.org/reference/starts_with.html" class="external-link">ends_with</a></span><span class="op">(</span><span class="st">"_mm"</span><span class="op">)</span>, </span>
+<span>    names_to <span class="op">=</span> <span class="st">"estimate_name"</span>, </span>
+<span>    values_to <span class="op">=</span> <span class="st">"estimate_value"</span></span>
+<span>  <span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>estimate_type <span class="op">=</span> <span class="st">"numeric"</span><span class="op">)</span></span>
+<span></span>
+<span><span class="co"># Creating a formatted flextable</span></span>
+<span><span class="fu"><a href="../reference/visTable.html">visTable</a></span><span class="op">(</span></span>
+<span>  result <span class="op">=</span> <span class="va">x</span>,</span>
+<span>  estimateName <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span></span>
+<span>    <span class="st">"Bill length - Bill depth (mm)"</span> <span class="op">=</span> <span class="st">"&lt;bill_length_mm&gt; - &lt;bill_depth_mm&gt;"</span>,</span>
+<span>    <span class="st">"Flipper length (mm)"</span> <span class="op">=</span> <span class="st">"&lt;flipper_length_mm&gt;"</span></span>
+<span>  <span class="op">)</span>,</span>
+<span>  header <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"species"</span>, <span class="st">"island"</span><span class="op">)</span>,</span>
+<span>  groupColumn <span class="op">=</span> <span class="st">"sex"</span>,</span>
+<span>  type <span class="op">=</span> <span class="st">"flextable"</span>,</span>
+<span>  hide <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"year"</span>, <span class="st">"estimate_type"</span><span class="op">)</span></span>
+<span><span class="op">)</span></span></code></pre></div>
+<div class="tabwid">
+<style>.cl-34407068{}.cl-3439d974{font-family:'Arial';font-size:10pt;font-weight:bold;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-3439d97e{font-family:'DejaVu Sans';font-size:11pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-343c7328{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-343c7332{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-343c733c{margin:0;text-align:right;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-343c924a{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.2pt solid rgba(190, 190, 190, 1.00);border-top: 1.2pt solid rgba(190, 190, 190, 1.00);border-left: 1.2pt solid rgba(190, 190, 190, 1.00);border-right: 1.2pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-343c9254{width:0.75in;background-color:rgba(217, 217, 217, 1.00);vertical-align: middle;border-bottom: 1.2pt solid rgba(190, 190, 190, 1.00);border-top: 1.2pt solid rgba(190, 190, 190, 1.00);border-left: 1.2pt solid rgba(190, 190, 190, 1.00);border-right: 1.2pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-343c9255{width:0.75in;background-color:rgba(225, 225, 225, 1.00);vertical-align: middle;border-bottom: 1.2pt solid rgba(190, 190, 190, 1.00);border-top: 1.2pt solid rgba(190, 190, 190, 1.00);border-left: 1.2pt solid rgba(190, 190, 190, 1.00);border-right: 1.2pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-343c925e{width:0.75in;background-color:rgba(233, 233, 233, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(190, 190, 190, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 1pt solid rgba(190, 190, 190, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-343c925f{width:0.75in;background-color:rgba(233, 233, 233, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(190, 190, 190, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 1pt solid rgba(190, 190, 190, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-343c9268{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 1pt solid rgba(190, 190, 190, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-343c9269{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-343c9272{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-343c9273{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1pt solid rgba(190, 190, 190, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 1pt solid rgba(190, 190, 190, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-343c927c{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1pt solid rgba(190, 190, 190, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-343c927d{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1pt solid rgba(190, 190, 190, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}</style>
+<table data-quarto-disable-processing="true" class="table cl-34407068">
+<thead>
+<tr style="overflow-wrap:break-word;">
+<th rowspan="4" class="cl-343c924a"><p class="cl-343c7328"><span class="cl-3439d974">Sex</span></p></th>
+<th rowspan="4" class="cl-343c924a"><p class="cl-343c7328"><span class="cl-3439d974">Estimate name</span></p></th>
+<th colspan="5" class="cl-343c9254"><p class="cl-343c7328"><span class="cl-3439d974">Species</span></p></th>
+</tr>
+<tr style="overflow-wrap:break-word;">
+<th colspan="3" class="cl-343c9255"><p class="cl-343c7328"><span class="cl-3439d974">Adelie</span></p></th>
+<th class="cl-343c9255"><p class="cl-343c7328"><span class="cl-3439d974">Gentoo</span></p></th>
+<th class="cl-343c9255"><p class="cl-343c7328"><span class="cl-3439d974">Chinstrap</span></p></th>
+</tr>
+<tr style="overflow-wrap:break-word;"><th colspan="5" class="cl-343c9254"><p class="cl-343c7328"><span class="cl-3439d974">Island</span></p></th></tr>
+<tr style="overflow-wrap:break-word;">
+<th class="cl-343c9255"><p class="cl-343c7328"><span class="cl-3439d974">Biscoe</span></p></th>
+<th class="cl-343c9255"><p class="cl-343c7328"><span class="cl-3439d974">Torgersen</span></p></th>
+<th class="cl-343c9255"><p class="cl-343c7328"><span class="cl-3439d974">Dream</span></p></th>
+<th class="cl-343c9255"><p class="cl-343c7328"><span class="cl-3439d974">Biscoe</span></p></th>
+<th class="cl-343c9255"><p class="cl-343c7328"><span class="cl-3439d974">Dream</span></p></th>
+</tr>
+</thead>
+<tbody>
+<tr style="overflow-wrap:break-word;">
+<td class="cl-343c925e"><p class="cl-343c7332"><span class="cl-3439d974">female</span></p></td>
+<td colspan="6" class="cl-343c925e"><p class="cl-343c7332"><span class="cl-3439d974"></span></p></td>
+</tr>
+<tr style="overflow-wrap:break-word;">
+<td class="cl-343c9268"><p class="cl-343c7332"><span class="cl-3439d97e"></span></p></td>
+<td class="cl-343c9269"><p class="cl-343c7332"><span class="cl-3439d97e">Bill length - Bill depth (mm)</span></p></td>
+<td class="cl-343c9272"><p class="cl-343c733c"><span class="cl-3439d97e">36.64 - 17.22</span></p></td>
+<td class="cl-343c9272"><p class="cl-343c733c"><span class="cl-3439d97e">36.61 - 17.40</span></p></td>
+<td class="cl-343c9272"><p class="cl-343c733c"><span class="cl-3439d97e">36.27 - 17.79</span></p></td>
+<td class="cl-343c9272"><p class="cl-343c733c"><span class="cl-3439d97e">45.30 - 14.13</span></p></td>
+<td class="cl-343c9272"><p class="cl-343c733c"><span class="cl-3439d97e">46.00 - 17.30</span></p></td>
+</tr>
+<tr style="overflow-wrap:break-word;">
+<td class="cl-343c9268"><p class="cl-343c7332"><span class="cl-3439d97e"></span></p></td>
+<td class="cl-343c9269"><p class="cl-343c7332"><span class="cl-3439d97e">Flipper length (mm)</span></p></td>
+<td class="cl-343c9272"><p class="cl-343c733c"><span class="cl-3439d97e">186.56</span></p></td>
+<td class="cl-343c9272"><p class="cl-343c733c"><span class="cl-3439d97e">190.00</span></p></td>
+<td class="cl-343c9272"><p class="cl-343c733c"><span class="cl-3439d97e">189.00</span></p></td>
+<td class="cl-343c9272"><p class="cl-343c733c"><span class="cl-3439d97e">213.00</span></p></td>
+<td class="cl-343c9272"><p class="cl-343c733c"><span class="cl-3439d97e">192.67</span></p></td>
+</tr>
+<tr style="overflow-wrap:break-word;">
+<td class="cl-343c925e"><p class="cl-343c7332"><span class="cl-3439d974">male</span></p></td>
+<td colspan="6" class="cl-343c925e"><p class="cl-343c7332"><span class="cl-3439d974"></span></p></td>
+</tr>
+<tr style="overflow-wrap:break-word;">
+<td class="cl-343c9268"><p class="cl-343c7332"><span class="cl-3439d97e"></span></p></td>
+<td class="cl-343c9269"><p class="cl-343c7332"><span class="cl-3439d97e">Bill length - Bill depth (mm)</span></p></td>
+<td class="cl-343c9272"><p class="cl-343c733c"><span class="cl-3439d97e">40.76 - 19.03</span></p></td>
+<td class="cl-343c9272"><p class="cl-343c733c"><span class="cl-3439d97e">40.92 - 18.84</span></p></td>
+<td class="cl-343c9272"><p class="cl-343c733c"><span class="cl-3439d97e">40.11 - 18.89</span></p></td>
+<td class="cl-343c9272"><p class="cl-343c733c"><span class="cl-3439d97e">48.54 - 15.70</span></p></td>
+<td class="cl-343c9272"><p class="cl-343c733c"><span class="cl-3439d97e">51.40 - 19.60</span></p></td>
+</tr>
+<tr style="overflow-wrap:break-word;">
+<td class="cl-343c9273"><p class="cl-343c7332"><span class="cl-3439d97e"></span></p></td>
+<td class="cl-343c927c"><p class="cl-343c7332"><span class="cl-3439d97e">Flipper length (mm)</span></p></td>
+<td class="cl-343c927d"><p class="cl-343c733c"><span class="cl-3439d97e">192.56</span></p></td>
+<td class="cl-343c927d"><p class="cl-343c733c"><span class="cl-3439d97e">193.50</span></p></td>
+<td class="cl-343c927d"><p class="cl-343c733c"><span class="cl-3439d97e">195.00</span></p></td>
+<td class="cl-343c927d"><p class="cl-343c733c"><span class="cl-3439d97e">222.09</span></p></td>
+<td class="cl-343c927d"><p class="cl-343c733c"><span class="cl-3439d97e">202.78</span></p></td>
+</tr>
+</tbody>
+</table>
+</div>
+</div>
+<div class="section level3">
+<h3 id="visomoptable">visOmopTable()<a class="anchor" aria-label="anchor" href="#visomoptable"></a>
+</h3>
+<p><code><a href="../reference/visOmopTable.html">visOmopTable()</a></code> extends the functionality of
+<code><a href="../reference/visTable.html">visTable()</a></code> with additional features tailored specifically
+for handling <code>&lt;summarised_result&gt;</code> objects, making it
+easier to work with standardized result formats.</p>
+<p>Let’s demonstrate <code><a href="../reference/visOmopTable.html">visOmopTable()</a></code> with a mock
+<code>&lt;summarised_result&gt;</code>:</p>
+<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="co"># Creating a mock summarised result</span></span>
+<span><span class="va">result</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/mockSummarisedResult.html">mockSummarisedResult</a></span><span class="op">(</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">strata_name</span> <span class="op">==</span> <span class="st">"age_group &amp;&amp;&amp; sex"</span><span class="op">)</span></span>
+<span></span>
+<span><span class="co"># Displaying the first few rows</span></span>
+<span><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">result</span><span class="op">)</span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 6 × 13</span></span></span>
+<span><span class="co">#&gt;   result_id cdm_name group_name  group_level strata_name       strata_level   </span></span>
+<span><span class="co">#&gt;       <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>       <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>       <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>             <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>          </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span>         1 mock     cohort_name cohort1     age_group &amp;&amp;&amp; sex &lt;40 &amp;&amp;&amp; Male   </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span>         1 mock     cohort_name cohort1     age_group &amp;&amp;&amp; sex &gt;=40 &amp;&amp;&amp; Male  </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span>         1 mock     cohort_name cohort1     age_group &amp;&amp;&amp; sex &lt;40 &amp;&amp;&amp; Female </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span>         1 mock     cohort_name cohort1     age_group &amp;&amp;&amp; sex &gt;=40 &amp;&amp;&amp; Female</span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">5</span>         1 mock     cohort_name cohort2     age_group &amp;&amp;&amp; sex &lt;40 &amp;&amp;&amp; Male   </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">6</span>         1 mock     cohort_name cohort2     age_group &amp;&amp;&amp; sex &gt;=40 &amp;&amp;&amp; Male  </span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 7 more variables: variable_name &lt;chr&gt;, variable_level &lt;chr&gt;,</span></span></span>
+<span><span class="co">#&gt; <span style="color: #949494;">#   estimate_name &lt;chr&gt;, estimate_type &lt;chr&gt;, estimate_value &lt;chr&gt;,</span></span></span>
+<span><span class="co">#&gt; <span style="color: #949494;">#   additional_name &lt;chr&gt;, additional_level &lt;chr&gt;</span></span></span>
+<span></span>
+<span><span class="co"># Creating a formatted gt table</span></span>
+<span><span class="fu"><a href="../reference/visOmopTable.html">visOmopTable</a></span><span class="op">(</span></span>
+<span>  result <span class="op">=</span> <span class="va">result</span>,</span>
+<span>  estimateName <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span></span>
+<span>    <span class="st">"N%"</span> <span class="op">=</span> <span class="st">"&lt;count&gt; (&lt;percentage&gt;)"</span>,</span>
+<span>    <span class="st">"N"</span> <span class="op">=</span> <span class="st">"&lt;count&gt;"</span>,</span>
+<span>    <span class="st">"Mean (SD)"</span> <span class="op">=</span> <span class="st">"&lt;mean&gt; (&lt;sd&gt;)"</span></span>
+<span>  <span class="op">)</span>,</span>
+<span>  header <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"package_name"</span>, <span class="st">"age_group"</span><span class="op">)</span>,</span>
+<span>  groupColumn <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"cohort_name"</span>, <span class="st">"sex"</span><span class="op">)</span>,</span>
+<span>  settingsColumn <span class="op">=</span> <span class="st">"package_name"</span>,</span>
+<span>  type <span class="op">=</span> <span class="st">"gt"</span></span>
+<span><span class="op">)</span></span></code></pre></div>
+<div id="mmyucmrwtk" style="padding-left:0px;padding-right:0px;padding-top:10px;padding-bottom:10px;overflow-x:auto;overflow-y:auto;width:auto;height:auto;">
+<style>#mmyucmrwtk table {
+  font-family: system-ui, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol', 'Noto Color Emoji';
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+}
+
+#mmyucmrwtk thead, #mmyucmrwtk tbody, #mmyucmrwtk tfoot, #mmyucmrwtk tr, #mmyucmrwtk td, #mmyucmrwtk th {
+  border-style: none;
+}
+
+#mmyucmrwtk p {
+  margin: 0;
+  padding: 0;
+}
+
+#mmyucmrwtk .gt_table {
+  display: table;
+  border-collapse: collapse;
+  line-height: normal;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  font-weight: normal;
+  font-style: normal;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#mmyucmrwtk .gt_caption {
+  padding-top: 4px;
+  padding-bottom: 4px;
+}
+
+#mmyucmrwtk .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#mmyucmrwtk .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 3px;
+  padding-bottom: 5px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#mmyucmrwtk .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#mmyucmrwtk .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#mmyucmrwtk .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#mmyucmrwtk .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#mmyucmrwtk .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#mmyucmrwtk .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#mmyucmrwtk .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#mmyucmrwtk .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 5px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#mmyucmrwtk .gt_spanner_row {
+  border-bottom-style: hidden;
+}
+
+#mmyucmrwtk .gt_group_heading {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  text-align: left;
+}
+
+#mmyucmrwtk .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#mmyucmrwtk .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#mmyucmrwtk .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#mmyucmrwtk .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#mmyucmrwtk .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#mmyucmrwtk .gt_stub_row_group {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 5px;
+  padding-right: 5px;
+  vertical-align: top;
+}
+
+#mmyucmrwtk .gt_row_group_first td {
+  border-top-width: 2px;
+}
+
+#mmyucmrwtk .gt_row_group_first th {
+  border-top-width: 2px;
+}
+
+#mmyucmrwtk .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#mmyucmrwtk .gt_first_summary_row {
+  border-top-style: solid;
+  border-top-color: #D3D3D3;
+}
+
+#mmyucmrwtk .gt_first_summary_row.thick {
+  border-top-width: 2px;
+}
+
+#mmyucmrwtk .gt_last_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#mmyucmrwtk .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#mmyucmrwtk .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#mmyucmrwtk .gt_last_grand_summary_row_top {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-bottom-style: double;
+  border-bottom-width: 6px;
+  border-bottom-color: #D3D3D3;
+}
+
+#mmyucmrwtk .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#mmyucmrwtk .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#mmyucmrwtk .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#mmyucmrwtk .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#mmyucmrwtk .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#mmyucmrwtk .gt_sourcenote {
+  font-size: 90%;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#mmyucmrwtk .gt_left {
+  text-align: left;
+}
+
+#mmyucmrwtk .gt_center {
+  text-align: center;
+}
+
+#mmyucmrwtk .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#mmyucmrwtk .gt_font_normal {
+  font-weight: normal;
+}
+
+#mmyucmrwtk .gt_font_bold {
+  font-weight: bold;
+}
+
+#mmyucmrwtk .gt_font_italic {
+  font-style: italic;
+}
+
+#mmyucmrwtk .gt_super {
+  font-size: 65%;
+}
+
+#mmyucmrwtk .gt_footnote_marks {
+  font-size: 75%;
+  vertical-align: 0.4em;
+  position: initial;
+}
+
+#mmyucmrwtk .gt_asterisk {
+  font-size: 100%;
+  vertical-align: 0;
+}
+
+#mmyucmrwtk .gt_indent_1 {
+  text-indent: 5px;
+}
+
+#mmyucmrwtk .gt_indent_2 {
+  text-indent: 10px;
+}
+
+#mmyucmrwtk .gt_indent_3 {
+  text-indent: 15px;
+}
+
+#mmyucmrwtk .gt_indent_4 {
+  text-indent: 20px;
+}
+
+#mmyucmrwtk .gt_indent_5 {
+  text-indent: 25px;
+}
+
+#mmyucmrwtk .katex-display {
+  display: inline-flex !important;
+  margin-bottom: 0.75em !important;
+}
+
+#mmyucmrwtk div.Reactable > div.rt-table > div.rt-thead > div.rt-tr.rt-tr-group-header > div.rt-th-group:after {
+  height: 0px !important;
+}
+</style>
+<table class="table gt_table" data-quarto-disable-processing="false" data-quarto-bootstrap="false">
+<thead>
+<tr class="gt_col_headings gt_spanner_row">
+<th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="4" style="background-color: #D9D9D9; text-align: center; font-weight: bold;" scope="colgroup"></th>
+      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="2" style="background-color: #D9D9D9; text-align: center; font-weight: bold;" scope="colgroup" id="spanner-[header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&lt;40">
+        <div class="gt_column_spanner">Package name</div>
+      </th>
+    </tr>
+<tr class="gt_col_headings gt_spanner_row">
+<th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="4" style="background-color: #E1E1E1; text-align: center; font-weight: bold;" scope="colgroup"></th>
+      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="2" style="background-color: #E1E1E1; text-align: center; font-weight: bold;" scope="colgroup" id="spanner-[header_level]visOmopResults
+[header_name]Age group
+[header_level]&lt;40">
+        <div class="gt_column_spanner">visOmopResults</div>
+      </th>
+    </tr>
+<tr class="gt_col_headings gt_spanner_row">
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1" style="text-align: center; font-weight: bold;" scope="col" id="CDM-name">CDM name</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1" style="text-align: center; font-weight: bold;" scope="col" id="Variable-name">Variable name</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1" style="text-align: center; font-weight: bold;" scope="col" id="Variable-level">Variable level</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1" style="text-align: center; font-weight: bold;" scope="col" id="Estimate-name">Estimate name</th>
+      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="2" style="background-color: #D9D9D9; text-align: center; font-weight: bold;" scope="colgroup" id="spanner-[header_name]Age group
+[header_level]&lt;40">
+        <div class="gt_column_spanner">Age group</div>
+      </th>
+    </tr>
+<tr class="gt_col_headings">
+<th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1" style="background-color: #E1E1E1; text-align: center; font-weight: bold;" scope="col" id="[header_name]Package-name-[header_level]visOmopResults-[header_name]Age-group-[header_level]&lt;40">&lt;40</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1" style="background-color: #E1E1E1; text-align: center; font-weight: bold;" scope="col" id="[header_name]Package-name-[header_level]visOmopResults-[header_name]Age-group-[header_level]&gt;=40">&gt;=40</th>
+    </tr>
+</thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<th colspan="6" class="gt_group_heading" style="background-color: #E9E9E9; font-weight: bold;" scope="colgroup" id="cohort1; Male">cohort1; Male</th>
+    </tr>
+<tr class="gt_row_group_first">
+<td headers="cohort1; Male  CDM name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">mock</td>
+<td headers="cohort1; Male  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">number subjects</td>
+<td headers="cohort1; Male  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="cohort1; Male  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N</td>
+<td headers="cohort1; Male  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&lt;40" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">3,203,857</td>
+<td headers="cohort1; Male  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&gt;=40" class="gt_row gt_right" style="text-align: right;">4,023,282</td>
+</tr>
+<tr>
+<td headers="cohort1; Male  CDM name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="cohort1; Male  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">age</td>
+<td headers="cohort1; Male  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="cohort1; Male  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Mean (SD)</td>
+<td headers="cohort1; Male  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&lt;40" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">22.56 (3.89)</td>
+<td headers="cohort1; Male  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&gt;=40" class="gt_row gt_right" style="text-align: right;">30.08 (4.61)</td>
+</tr>
+<tr>
+<td headers="cohort1; Male  CDM name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="cohort1; Male  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Medications</td>
+<td headers="cohort1; Male  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Amoxiciline</td>
+<td headers="cohort1; Male  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N%</td>
+<td headers="cohort1; Male  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&lt;40" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">54,248 (92.00)</td>
+<td headers="cohort1; Male  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&gt;=40" class="gt_row gt_right" style="text-align: right;">54,460 (40.07)</td>
+</tr>
+<tr>
+<td headers="cohort1; Male  CDM name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="cohort1; Male  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="cohort1; Male  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Ibuprofen</td>
+<td headers="cohort1; Male  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N%</td>
+<td headers="cohort1; Male  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&lt;40" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">21,843 (56.69)</td>
+<td headers="cohort1; Male  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&gt;=40" class="gt_row gt_right" style="text-align: right;">41,836 (25.30)</td>
+</tr>
+<tr class="gt_group_heading_row">
+<th colspan="6" class="gt_group_heading" style="background-color: #E9E9E9; font-weight: bold;" scope="colgroup" id="cohort1; Female">cohort1; Female</th>
+    </tr>
+<tr class="gt_row_group_first">
+<td headers="cohort1; Female  CDM name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">mock</td>
+<td headers="cohort1; Female  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">number subjects</td>
+<td headers="cohort1; Female  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="cohort1; Female  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N</td>
+<td headers="cohort1; Female  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&lt;40" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">1,956,698</td>
+<td headers="cohort1; Female  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&gt;=40" class="gt_row gt_right" style="text-align: right;">4,035,381</td>
+</tr>
+<tr>
+<td headers="cohort1; Female  CDM name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="cohort1; Female  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">age</td>
+<td headers="cohort1; Female  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="cohort1; Female  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Mean (SD)</td>
+<td headers="cohort1; Female  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&lt;40" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">63.65 (3.15)</td>
+<td headers="cohort1; Female  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&gt;=40" class="gt_row gt_right" style="text-align: right;">47.90 (1.75)</td>
+</tr>
+<tr>
+<td headers="cohort1; Female  CDM name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="cohort1; Female  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Medications</td>
+<td headers="cohort1; Female  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Amoxiciline</td>
+<td headers="cohort1; Female  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N%</td>
+<td headers="cohort1; Female  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&lt;40" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">27,860 (21.32)</td>
+<td headers="cohort1; Female  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&gt;=40" class="gt_row gt_right" style="text-align: right;">44,670 (67.18)</td>
+</tr>
+<tr>
+<td headers="cohort1; Female  CDM name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="cohort1; Female  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="cohort1; Female  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Ibuprofen</td>
+<td headers="cohort1; Female  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N%</td>
+<td headers="cohort1; Female  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&lt;40" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">66,887 (91.88)</td>
+<td headers="cohort1; Female  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&gt;=40" class="gt_row gt_right" style="text-align: right;">50,765 (86.74)</td>
+</tr>
+<tr class="gt_group_heading_row">
+<th colspan="6" class="gt_group_heading" style="background-color: #E9E9E9; font-weight: bold;" scope="colgroup" id="cohort2; Male">cohort2; Male</th>
+    </tr>
+<tr class="gt_row_group_first">
+<td headers="cohort2; Male  CDM name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">mock</td>
+<td headers="cohort2; Male  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">number subjects</td>
+<td headers="cohort2; Male  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="cohort2; Male  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N</td>
+<td headers="cohort2; Male  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&lt;40" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">7,353,196</td>
+<td headers="cohort2; Male  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&gt;=40" class="gt_row gt_right" style="text-align: right;">1,959,567</td>
+</tr>
+<tr>
+<td headers="cohort2; Male  CDM name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="cohort2; Male  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">age</td>
+<td headers="cohort2; Male  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="cohort2; Male  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Mean (SD)</td>
+<td headers="cohort2; Male  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&lt;40" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">68.02 (0.65)</td>
+<td headers="cohort2; Male  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&gt;=40" class="gt_row gt_right" style="text-align: right;">49.88 (3.54)</td>
+</tr>
+<tr>
+<td headers="cohort2; Male  CDM name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="cohort2; Male  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Medications</td>
+<td headers="cohort2; Male  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Amoxiciline</td>
+<td headers="cohort2; Male  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N%</td>
+<td headers="cohort2; Male  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&lt;40" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">37,697 (71.83)</td>
+<td headers="cohort2; Male  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&gt;=40" class="gt_row gt_right" style="text-align: right;">55,991 (24.13)</td>
+</tr>
+<tr>
+<td headers="cohort2; Male  CDM name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="cohort2; Male  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="cohort2; Male  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Ibuprofen</td>
+<td headers="cohort2; Male  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N%</td>
+<td headers="cohort2; Male  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&lt;40" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">1,148 (16.46)</td>
+<td headers="cohort2; Male  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&gt;=40" class="gt_row gt_right" style="text-align: right;">88,825 (66.32)</td>
+</tr>
+<tr class="gt_group_heading_row">
+<th colspan="6" class="gt_group_heading" style="background-color: #E9E9E9; font-weight: bold;" scope="colgroup" id="cohort2; Female">cohort2; Female</th>
+    </tr>
+<tr class="gt_row_group_first">
+<td headers="cohort2; Female  CDM name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">mock</td>
+<td headers="cohort2; Female  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">number subjects</td>
+<td headers="cohort2; Female  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="cohort2; Female  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N</td>
+<td headers="cohort2; Female  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&lt;40" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">9,805,397</td>
+<td headers="cohort2; Female  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&gt;=40" class="gt_row gt_right" style="text-align: right;">7,415,215</td>
+</tr>
+<tr>
+<td headers="cohort2; Female  CDM name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="cohort2; Female  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">age</td>
+<td headers="cohort2; Female  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="cohort2; Female  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Mean (SD)</td>
+<td headers="cohort2; Female  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&lt;40" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">64.17 (8.25)</td>
+<td headers="cohort2; Female  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&gt;=40" class="gt_row gt_right" style="text-align: right;">66.03 (2.74)</td>
+</tr>
+<tr>
+<td headers="cohort2; Female  CDM name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="cohort2; Female  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Medications</td>
+<td headers="cohort2; Female  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Amoxiciline</td>
+<td headers="cohort2; Female  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N%</td>
+<td headers="cohort2; Female  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&lt;40" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">85,708 (54.70)</td>
+<td headers="cohort2; Female  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&gt;=40" class="gt_row gt_right" style="text-align: right;">38,481 (83.48)</td>
+</tr>
+<tr>
+<td headers="cohort2; Female  CDM name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="cohort2; Female  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="cohort2; Female  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Ibuprofen</td>
+<td headers="cohort2; Female  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N%</td>
+<td headers="cohort2; Female  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&lt;40" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">99,635 (85.66)</td>
+<td headers="cohort2; Female  [header_name]Package name
+[header_level]visOmopResults
+[header_name]Age group
+[header_level]&gt;=40" class="gt_row gt_right" style="text-align: right;">50,019 (92.65)</td>
+</tr>
+</tbody>
+</table>
+</div>
+<p>The workflow is quite similar to <code><a href="../reference/visTable.html">visTable()</a></code>, but it
+includes specific enhancements for
+<code>&lt;summarised_result&gt;</code> objects:</p>
+<ul>
+<li><p><strong>Automatic splitting</strong>: The result object is always
+processed using the <a href="https://darwin-eu.github.io/visOmopResults/reference/splitAll.html"><code>splitAll()</code></a>
+function. Thereby, column names to use in other arguments must be based
+on the split result.</p></li>
+<li><p><strong><code>settingsColumn</code> argument</strong>: Use this
+argument to specify which settings should be displayed in the main
+table. The columns specified here can also be referenced in other
+arguments such as <code>header</code>, <code>rename</code>, and
+<code>groupColumn.</code></p></li>
+<li><p><strong><code>header</code> argument</strong>: accepts specific
+<code>&lt;summarised_result&gt;</code> inputs, in addition to its
+typical usage as in <code><a href="../reference/visTable.html">visTable()</a></code>. For example, use “strata”
+in the header to display all variables in <code>strata_name</code>, or
+use “settings” to show all settings specified in
+<code>settingsColumns.</code></p></li>
+<li><p><strong>Hidden columns</strong>: result_id and estimate_type
+columns are always hidden as they serve as helper columns for internal
+processes.</p></li>
+<li><p><strong>Suppressed estimates</strong>: if the result object has
+been processed with <a href="https://darwin-eu-dev.github.io/omopgenerics/reference/suppress.html" class="external-link">suppress()</a>,
+obscured estimates can be displayed as the default <code>na</code> value
+or as “&lt;{minCellCount}” with the corresponding minimum count value
+used. This can be controlled using the <code>showMinCellCount</code>
+argument.</p></li>
+</ul>
+<p>In the next example, <code><a href="../reference/visOmopTable.html">visOmopTable()</a></code> generates a
+<code>&lt;gt&gt;</code> table while displaying suppressed estimates
+(those with counts below 1,000,000) with the specified minimum cell
+count.</p>
+<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="va">result</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://darwin-eu.github.io/omopgenerics/reference/suppress.html" class="external-link">suppress</a></span><span class="op">(</span>minCellCount <span class="op">=</span> <span class="fl">1000000</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="../reference/visOmopTable.html">visOmopTable</a></span><span class="op">(</span></span>
+<span>    estimateName <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span></span>
+<span>      <span class="st">"N%"</span> <span class="op">=</span> <span class="st">"&lt;count&gt; (&lt;percentage&gt;)"</span>,</span>
+<span>      <span class="st">"N"</span> <span class="op">=</span> <span class="st">"&lt;count&gt;"</span>,</span>
+<span>      <span class="st">"Mean (SD)"</span> <span class="op">=</span> <span class="st">"&lt;mean&gt; (&lt;sd&gt;)"</span></span>
+<span>    <span class="op">)</span>,</span>
+<span>    header <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"My visOmopTable"</span>, <span class="st">"group"</span><span class="op">)</span>,</span>
+<span>    groupColumn <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"strata"</span><span class="op">)</span>,</span>
+<span>    hide <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"cdm_name"</span><span class="op">)</span>,</span>
+<span>    showMinCellCount <span class="op">=</span> <span class="cn">TRUE</span>,</span>
+<span>    type <span class="op">=</span> <span class="st">"gt"</span></span>
+<span>  <span class="op">)</span></span></code></pre></div>
+<div id="dbirslsqjl" style="padding-left:0px;padding-right:0px;padding-top:10px;padding-bottom:10px;overflow-x:auto;overflow-y:auto;width:auto;height:auto;">
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+
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+
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+}
+
+#dbirslsqjl .gt_footnotes {
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+
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+
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+
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+  text-indent: 25px;
+}
+
+#dbirslsqjl .katex-display {
+  display: inline-flex !important;
+  margin-bottom: 0.75em !important;
+}
+
+#dbirslsqjl div.Reactable > div.rt-table > div.rt-thead > div.rt-tr.rt-tr-group-header > div.rt-th-group:after {
+  height: 0px !important;
+}
+</style>
+<table class="table gt_table" data-quarto-disable-processing="false" data-quarto-bootstrap="false">
+<thead>
+<tr class="gt_col_headings gt_spanner_row">
+<th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="3" style="background-color: #C8C8C8; text-align: center; font-weight: bold;" scope="colgroup"></th>
+      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="2" style="background-color: #C8C8C8; text-align: center; font-weight: bold;" scope="colgroup" id="spanner-[header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort1">
+        <div class="gt_column_spanner">My visOmopTable</div>
+      </th>
+    </tr>
+<tr class="gt_col_headings gt_spanner_row">
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1" style="text-align: center; font-weight: bold;" scope="col" id="Variable-name">Variable name</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1" style="text-align: center; font-weight: bold;" scope="col" id="Variable-level">Variable level</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1" style="text-align: center; font-weight: bold;" scope="col" id="Estimate-name">Estimate name</th>
+      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="2" style="background-color: #D9D9D9; text-align: center; font-weight: bold;" scope="colgroup" id="spanner-[header_name]Cohort name
+[header_level]cohort1">
+        <div class="gt_column_spanner">Cohort name</div>
+      </th>
+    </tr>
+<tr class="gt_col_headings">
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1" style="background-color: #E1E1E1; text-align: center; font-weight: bold;" scope="col" id="[header]My-visOmopTable-[header_name]Cohort-name-[header_level]cohort1">cohort1</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1" style="background-color: #E1E1E1; text-align: center; font-weight: bold;" scope="col" id="[header]My-visOmopTable-[header_name]Cohort-name-[header_level]cohort2">cohort2</th>
+    </tr>
+</thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<th colspan="5" class="gt_group_heading" style="background-color: #E9E9E9; font-weight: bold;" scope="colgroup" id="&amp;lt;40; Male">&lt;40; Male</th>
+    </tr>
+<tr class="gt_row_group_first">
+<td headers="&lt;40; Male  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">number subjects</td>
+<td headers="&lt;40; Male  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="&lt;40; Male  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N</td>
+<td headers="&lt;40; Male  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort1" class="gt_row gt_left" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">3,203,857</td>
+<td headers="&lt;40; Male  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort2" class="gt_row gt_left" style="text-align: right;">7,353,196</td>
+</tr>
+<tr>
+<td headers="&lt;40; Male  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">age</td>
+<td headers="&lt;40; Male  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="&lt;40; Male  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Mean (SD)</td>
+<td headers="&lt;40; Male  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort1" class="gt_row gt_left" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">22.56 (3.89)</td>
+<td headers="&lt;40; Male  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort2" class="gt_row gt_left" style="text-align: right;">68.02 (0.65)</td>
+</tr>
+<tr>
+<td headers="&lt;40; Male  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Medications</td>
+<td headers="&lt;40; Male  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Amoxiciline</td>
+<td headers="&lt;40; Male  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N%</td>
+<td headers="&lt;40; Male  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort1" class="gt_row gt_left" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">&lt;1,000,000 (&lt;1,000,000)</td>
+<td headers="&lt;40; Male  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort2" class="gt_row gt_left" style="text-align: right;">&lt;1,000,000 (&lt;1,000,000)</td>
+</tr>
+<tr>
+<td headers="&lt;40; Male  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="&lt;40; Male  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Ibuprofen</td>
+<td headers="&lt;40; Male  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N%</td>
+<td headers="&lt;40; Male  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort1" class="gt_row gt_left" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">&lt;1,000,000 (&lt;1,000,000)</td>
+<td headers="&lt;40; Male  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort2" class="gt_row gt_left" style="text-align: right;">&lt;1,000,000 (&lt;1,000,000)</td>
+</tr>
+<tr class="gt_group_heading_row">
+<th colspan="5" class="gt_group_heading" style="background-color: #E9E9E9; font-weight: bold;" scope="colgroup" id="&amp;gt;=40; Male">&gt;=40; Male</th>
+    </tr>
+<tr class="gt_row_group_first">
+<td headers="&gt;=40; Male  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">number subjects</td>
+<td headers="&gt;=40; Male  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="&gt;=40; Male  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N</td>
+<td headers="&gt;=40; Male  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort1" class="gt_row gt_left" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">4,023,282</td>
+<td headers="&gt;=40; Male  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort2" class="gt_row gt_left" style="text-align: right;">1,959,567</td>
+</tr>
+<tr>
+<td headers="&gt;=40; Male  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">age</td>
+<td headers="&gt;=40; Male  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="&gt;=40; Male  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Mean (SD)</td>
+<td headers="&gt;=40; Male  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort1" class="gt_row gt_left" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">30.08 (4.61)</td>
+<td headers="&gt;=40; Male  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort2" class="gt_row gt_left" style="text-align: right;">49.88 (3.54)</td>
+</tr>
+<tr>
+<td headers="&gt;=40; Male  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Medications</td>
+<td headers="&gt;=40; Male  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Amoxiciline</td>
+<td headers="&gt;=40; Male  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N%</td>
+<td headers="&gt;=40; Male  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort1" class="gt_row gt_left" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">&lt;1,000,000 (&lt;1,000,000)</td>
+<td headers="&gt;=40; Male  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort2" class="gt_row gt_left" style="text-align: right;">&lt;1,000,000 (&lt;1,000,000)</td>
+</tr>
+<tr>
+<td headers="&gt;=40; Male  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="&gt;=40; Male  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Ibuprofen</td>
+<td headers="&gt;=40; Male  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N%</td>
+<td headers="&gt;=40; Male  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort1" class="gt_row gt_left" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">&lt;1,000,000 (&lt;1,000,000)</td>
+<td headers="&gt;=40; Male  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort2" class="gt_row gt_left" style="text-align: right;">&lt;1,000,000 (&lt;1,000,000)</td>
+</tr>
+<tr class="gt_group_heading_row">
+<th colspan="5" class="gt_group_heading" style="background-color: #E9E9E9; font-weight: bold;" scope="colgroup" id="&amp;lt;40; Female">&lt;40; Female</th>
+    </tr>
+<tr class="gt_row_group_first">
+<td headers="&lt;40; Female  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">number subjects</td>
+<td headers="&lt;40; Female  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="&lt;40; Female  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N</td>
+<td headers="&lt;40; Female  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort1" class="gt_row gt_left" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">1,956,698</td>
+<td headers="&lt;40; Female  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort2" class="gt_row gt_left" style="text-align: right;">9,805,397</td>
+</tr>
+<tr>
+<td headers="&lt;40; Female  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">age</td>
+<td headers="&lt;40; Female  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="&lt;40; Female  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Mean (SD)</td>
+<td headers="&lt;40; Female  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort1" class="gt_row gt_left" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">63.65 (3.15)</td>
+<td headers="&lt;40; Female  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort2" class="gt_row gt_left" style="text-align: right;">64.17 (8.25)</td>
+</tr>
+<tr>
+<td headers="&lt;40; Female  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Medications</td>
+<td headers="&lt;40; Female  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Amoxiciline</td>
+<td headers="&lt;40; Female  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N%</td>
+<td headers="&lt;40; Female  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort1" class="gt_row gt_left" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">&lt;1,000,000 (&lt;1,000,000)</td>
+<td headers="&lt;40; Female  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort2" class="gt_row gt_left" style="text-align: right;">&lt;1,000,000 (&lt;1,000,000)</td>
+</tr>
+<tr>
+<td headers="&lt;40; Female  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="&lt;40; Female  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Ibuprofen</td>
+<td headers="&lt;40; Female  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N%</td>
+<td headers="&lt;40; Female  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort1" class="gt_row gt_left" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">&lt;1,000,000 (&lt;1,000,000)</td>
+<td headers="&lt;40; Female  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort2" class="gt_row gt_left" style="text-align: right;">&lt;1,000,000 (&lt;1,000,000)</td>
+</tr>
+<tr class="gt_group_heading_row">
+<th colspan="5" class="gt_group_heading" style="background-color: #E9E9E9; font-weight: bold;" scope="colgroup" id="&amp;gt;=40; Female">&gt;=40; Female</th>
+    </tr>
+<tr class="gt_row_group_first">
+<td headers="&gt;=40; Female  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">number subjects</td>
+<td headers="&gt;=40; Female  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="&gt;=40; Female  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N</td>
+<td headers="&gt;=40; Female  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort1" class="gt_row gt_left" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">4,035,381</td>
+<td headers="&gt;=40; Female  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort2" class="gt_row gt_left" style="text-align: right;">7,415,215</td>
+</tr>
+<tr>
+<td headers="&gt;=40; Female  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">age</td>
+<td headers="&gt;=40; Female  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="&gt;=40; Female  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Mean (SD)</td>
+<td headers="&gt;=40; Female  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort1" class="gt_row gt_left" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">47.90 (1.75)</td>
+<td headers="&gt;=40; Female  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort2" class="gt_row gt_left" style="text-align: right;">66.03 (2.74)</td>
+</tr>
+<tr>
+<td headers="&gt;=40; Female  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Medications</td>
+<td headers="&gt;=40; Female  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Amoxiciline</td>
+<td headers="&gt;=40; Female  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N%</td>
+<td headers="&gt;=40; Female  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort1" class="gt_row gt_left" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">&lt;1,000,000 (&lt;1,000,000)</td>
+<td headers="&gt;=40; Female  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort2" class="gt_row gt_left" style="text-align: right;">&lt;1,000,000 (&lt;1,000,000)</td>
+</tr>
+<tr>
+<td headers="&gt;=40; Female  Variable name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="&gt;=40; Female  Variable level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Ibuprofen</td>
+<td headers="&gt;=40; Female  Estimate name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N%</td>
+<td headers="&gt;=40; Female  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort1" class="gt_row gt_left" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">&lt;1,000,000 (&lt;1,000,000)</td>
+<td headers="&gt;=40; Female  [header]My visOmopTable
+[header_name]Cohort name
+[header_level]cohort2" class="gt_row gt_left" style="text-align: right;">&lt;1,000,000 (&lt;1,000,000)</td>
+</tr>
+</tbody>
+</table>
+</div>
+</div>
+<div class="section level3">
+<h3 id="styling-tables">Styling tables<a class="anchor" aria-label="anchor" href="#styling-tables"></a>
+</h3>
+<p>Tables displayed in <code><a href="../reference/visOmopResults-package.html">visOmopResults()</a></code> follow a default
+style, but customisation is possible through the <code>.options</code>
+argument. This argument allows users to modify various formatting
+aspects using options from the <code>format</code> functions (see the
+<em><code>format</code> Functions</em> section to learn more).</p>
+<p>The table below details which <code>format</code> function each
+styling option belongs to, along with a description of each option:</p>
+<div id="mpgudacgqf" style="padding-left:0px;padding-right:0px;padding-top:10px;padding-bottom:10px;overflow-x:auto;overflow-y:auto;width:auto;height:auto;">
+<style>#mpgudacgqf table {
+  font-family: system-ui, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol', 'Noto Color Emoji';
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+}
+
+#mpgudacgqf thead, #mpgudacgqf tbody, #mpgudacgqf tfoot, #mpgudacgqf tr, #mpgudacgqf td, #mpgudacgqf th {
+  border-style: none;
+}
+
+#mpgudacgqf p {
+  margin: 0;
+  padding: 0;
+}
+
+#mpgudacgqf .gt_table {
+  display: table;
+  border-collapse: collapse;
+  line-height: normal;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  font-weight: normal;
+  font-style: normal;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#mpgudacgqf .gt_caption {
+  padding-top: 4px;
+  padding-bottom: 4px;
+}
+
+#mpgudacgqf .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#mpgudacgqf .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 3px;
+  padding-bottom: 5px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#mpgudacgqf .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#mpgudacgqf .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#mpgudacgqf .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#mpgudacgqf .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#mpgudacgqf .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#mpgudacgqf .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#mpgudacgqf .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#mpgudacgqf .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 5px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#mpgudacgqf .gt_spanner_row {
+  border-bottom-style: hidden;
+}
+
+#mpgudacgqf .gt_group_heading {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  text-align: left;
+}
+
+#mpgudacgqf .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#mpgudacgqf .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#mpgudacgqf .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#mpgudacgqf .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#mpgudacgqf .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#mpgudacgqf .gt_stub_row_group {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 5px;
+  padding-right: 5px;
+  vertical-align: top;
+}
+
+#mpgudacgqf .gt_row_group_first td {
+  border-top-width: 2px;
+}
+
+#mpgudacgqf .gt_row_group_first th {
+  border-top-width: 2px;
+}
+
+#mpgudacgqf .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#mpgudacgqf .gt_first_summary_row {
+  border-top-style: solid;
+  border-top-color: #D3D3D3;
+}
+
+#mpgudacgqf .gt_first_summary_row.thick {
+  border-top-width: 2px;
+}
+
+#mpgudacgqf .gt_last_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#mpgudacgqf .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#mpgudacgqf .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#mpgudacgqf .gt_last_grand_summary_row_top {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-bottom-style: double;
+  border-bottom-width: 6px;
+  border-bottom-color: #D3D3D3;
+}
+
+#mpgudacgqf .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#mpgudacgqf .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#mpgudacgqf .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#mpgudacgqf .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#mpgudacgqf .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#mpgudacgqf .gt_sourcenote {
+  font-size: 90%;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#mpgudacgqf .gt_left {
+  text-align: left;
+}
+
+#mpgudacgqf .gt_center {
+  text-align: center;
+}
+
+#mpgudacgqf .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#mpgudacgqf .gt_font_normal {
+  font-weight: normal;
+}
+
+#mpgudacgqf .gt_font_bold {
+  font-weight: bold;
+}
+
+#mpgudacgqf .gt_font_italic {
+  font-style: italic;
+}
+
+#mpgudacgqf .gt_super {
+  font-size: 65%;
+}
+
+#mpgudacgqf .gt_footnote_marks {
+  font-size: 75%;
+  vertical-align: 0.4em;
+  position: initial;
+}
+
+#mpgudacgqf .gt_asterisk {
+  font-size: 100%;
+  vertical-align: 0;
+}
+
+#mpgudacgqf .gt_indent_1 {
+  text-indent: 5px;
+}
+
+#mpgudacgqf .gt_indent_2 {
+  text-indent: 10px;
+}
+
+#mpgudacgqf .gt_indent_3 {
+  text-indent: 15px;
+}
+
+#mpgudacgqf .gt_indent_4 {
+  text-indent: 20px;
+}
+
+#mpgudacgqf .gt_indent_5 {
+  text-indent: 25px;
+}
+
+#mpgudacgqf .katex-display {
+  display: inline-flex !important;
+  margin-bottom: 0.75em !important;
+}
+
+#mpgudacgqf div.Reactable > div.rt-table > div.rt-thead > div.rt-tr.rt-tr-group-header > div.rt-th-group:after {
+  height: 0px !important;
+}
+</style>
+<table class="table gt_table" data-quarto-disable-processing="false" data-quarto-bootstrap="false">
+<thead><tr class="gt_col_headings">
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1" style="text-align: center; font-weight: bold;" scope="col" id="Argument">Argument</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="1" colspan="1" style="text-align: center; font-weight: bold;" scope="col" id="Description">Description</th>
+    </tr></thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<th colspan="2" class="gt_group_heading" style="background-color: #E9E9E9; font-weight: bold;" scope="colgroup" id="formatEstimateValue()">formatEstimateValue()</th>
+    </tr>
+<tr class="gt_row_group_first">
+<td headers="formatEstimateValue()  Argument" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">decimals</td>
+<td headers="formatEstimateValue()  Description" class="gt_row gt_left" style="text-align: left;">Number of decimals per estimate type (integer, numeric, percentage, proportion), estimate name, or all estimate values (introduce the number of decimals).</td>
+</tr>
+<tr>
+<td headers="formatEstimateValue()  Argument" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">decimalMark</td>
+<td headers="formatEstimateValue()  Description" class="gt_row gt_left" style="text-align: left;">Decimal separator mark.</td>
+</tr>
+<tr>
+<td headers="formatEstimateValue()  Argument" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">bigMark</td>
+<td headers="formatEstimateValue()  Description" class="gt_row gt_left" style="text-align: left;">Thousand and millions separator mark.</td>
+</tr>
+<tr class="gt_group_heading_row">
+<th colspan="2" class="gt_group_heading" style="background-color: #E9E9E9; font-weight: bold;" scope="colgroup" id="formatEstimateName()">formatEstimateName()</th>
+    </tr>
+<tr class="gt_row_group_first">
+<td headers="formatEstimateName()  Argument" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">keepNotFormatted</td>
+<td headers="formatEstimateName()  Description" class="gt_row gt_left" style="text-align: left;">Whether to keep rows not formatted.</td>
+</tr>
+<tr>
+<td headers="formatEstimateName()  Argument" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">useFormatOrder</td>
+<td headers="formatEstimateName()  Description" class="gt_row gt_left" style="text-align: left;">Whether to use the order in which estimate names appear in the estimateName (TRUE), or use the order in the input dataframe (FALSE).</td>
+</tr>
+<tr class="gt_group_heading_row">
+<th colspan="2" class="gt_group_heading" style="background-color: #E9E9E9; font-weight: bold;" scope="colgroup" id="formatHeader()">formatHeader()</th>
+    </tr>
+<tr class="gt_row_group_first">
+<td headers="formatHeader()  Argument" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">delim</td>
+<td headers="formatHeader()  Description" class="gt_row gt_left" style="text-align: left;">Delimiter to use to separate headers.</td>
+</tr>
+<tr>
+<td headers="formatHeader()  Argument" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">includeHeaderName</td>
+<td headers="formatHeader()  Description" class="gt_row gt_left" style="text-align: left;">Whether to include the column name as header.</td>
+</tr>
+<tr>
+<td headers="formatHeader()  Argument" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">includeHeaderKey</td>
+<td headers="formatHeader()  Description" class="gt_row gt_left" style="text-align: left;">Whether to include the header key (header, header_name, header_level) before each header type in the column names.</td>
+</tr>
+<tr class="gt_group_heading_row">
+<th colspan="2" class="gt_group_heading" style="background-color: #E9E9E9; font-weight: bold;" scope="colgroup" id="formatTable()">formatTable()</th>
+    </tr>
+<tr class="gt_row_group_first">
+<td headers="formatTable()  Argument" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">style</td>
+<td headers="formatTable()  Description" class="gt_row gt_left" style="text-align: left;">Named list that specifies how to style the different parts of the gt or flextable table generated. Accepted style entries are: title, subtitle, header, header_name, header_level, column_name, group_label, and body. Alternatively, use 'default' to get visOmopResults style, or NULL for gt/flextable style. Keep in mind that styling code is different for gt and flextable. To see the 'deafult' gt style code use gtStyle(), and flextableStyle() for flextable default code style</td>
+</tr>
+<tr>
+<td headers="formatTable()  Argument" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">na</td>
+<td headers="formatTable()  Description" class="gt_row gt_left" style="text-align: left;">How to display missing values.</td>
+</tr>
+<tr>
+<td headers="formatTable()  Argument" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">title</td>
+<td headers="formatTable()  Description" class="gt_row gt_left" style="text-align: left;">Title of the table, or NULL for no title.</td>
+</tr>
+<tr>
+<td headers="formatTable()  Argument" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">subtitle</td>
+<td headers="formatTable()  Description" class="gt_row gt_left" style="text-align: left;">Subtitle of the table, or NULL for no subtitle.</td>
+</tr>
+<tr>
+<td headers="formatTable()  Argument" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">caption</td>
+<td headers="formatTable()  Description" class="gt_row gt_left" style="text-align: left;">Caption for the table, or NULL for no caption. Text in markdown formatting style (e.g. ⁠*Your caption here*⁠ for caption in italics)</td>
+</tr>
+<tr>
+<td headers="formatTable()  Argument" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">groupAsColumn</td>
+<td headers="formatTable()  Description" class="gt_row gt_left" style="text-align: left;">Whether to display the group labels as a column (TRUE) or rows (FALSE).</td>
+</tr>
+<tr>
+<td headers="formatTable()  Argument" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">groupOrder</td>
+<td headers="formatTable()  Description" class="gt_row gt_left" style="text-align: left;">Order in which to display group labels.</td>
+</tr>
+<tr>
+<td headers="formatTable()  Argument" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">merge</td>
+<td headers="formatTable()  Description" class="gt_row gt_left" style="text-align: left;">Names of the columns to merge vertically when consecutive row cells have identical values. Alternatively, use 'all_columns' to apply this merging to all columns, or use NULL to indicate no merging.</td>
+</tr>
+</tbody>
+</table>
+</div>
+<p>To view the default <code>.options</code> settings used in
+<code>vis</code> tables, use the following function:</p>
+<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="fu"><a href="../reference/tableOptions.html">tableOptions</a></span><span class="op">(</span><span class="op">)</span></span>
+<span><span class="co">#&gt; $decimals</span></span>
+<span><span class="co">#&gt;    integer percentage    numeric proportion </span></span>
+<span><span class="co">#&gt;          0          2          2          2 </span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; $decimalMark</span></span>
+<span><span class="co">#&gt; [1] "."</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; $bigMark</span></span>
+<span><span class="co">#&gt; [1] ","</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; $keepNotFormatted</span></span>
+<span><span class="co">#&gt; [1] TRUE</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; $useFormatOrder</span></span>
+<span><span class="co">#&gt; [1] TRUE</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; $delim</span></span>
+<span><span class="co">#&gt; [1] "\n"</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; $includeHeaderName</span></span>
+<span><span class="co">#&gt; [1] TRUE</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; $includeHeaderKey</span></span>
+<span><span class="co">#&gt; [1] TRUE</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; $style</span></span>
+<span><span class="co">#&gt; [1] "default"</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; $na</span></span>
+<span><span class="co">#&gt; [1] "-"</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; $title</span></span>
+<span><span class="co">#&gt; NULL</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; $subtitle</span></span>
+<span><span class="co">#&gt; NULL</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; $caption</span></span>
+<span><span class="co">#&gt; NULL</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; $groupAsColumn</span></span>
+<span><span class="co">#&gt; [1] FALSE</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; $groupOrder</span></span>
+<span><span class="co">#&gt; NULL</span></span>
+<span><span class="co">#&gt; </span></span>
+<span><span class="co">#&gt; $merge</span></span>
+<span><span class="co">#&gt; [1] "all_columns"</span></span></code></pre></div>
+<div class="section level4">
+<h4 id="styling-tables-1">Styling tables<a class="anchor" aria-label="anchor" href="#styling-tables-1"></a>
+</h4>
+<p>To inspect the code for the default styles of the different table
+types supported, you can use the following function:</p>
+<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="fu"><a href="../reference/tableStyle.html">tableStyle</a></span><span class="op">(</span>type <span class="op">=</span> <span class="st">"gt"</span><span class="op">)</span></span>
+<span><span class="co">#&gt; list(header = list(gt::cell_fill(color = "#c8c8c8"), gt::cell_text(weight = "bold", </span></span>
+<span><span class="co">#&gt;     align = "center")), header_name = list(gt::cell_fill(color = "#d9d9d9"), </span></span>
+<span><span class="co">#&gt;     gt::cell_text(weight = "bold", align = "center")), header_level = list(gt::cell_fill(color = "#e1e1e1"), </span></span>
+<span><span class="co">#&gt;     gt::cell_text(weight = "bold", align = "center")), column_name = list(gt::cell_text(weight = "bold", </span></span>
+<span><span class="co">#&gt;     align = "center")), group_label = list(gt::cell_fill(color = "#e9e9e9"), </span></span>
+<span><span class="co">#&gt;     gt::cell_text(weight = "bold")), title = list(gt::cell_text(weight = "bold", </span></span>
+<span><span class="co">#&gt;     size = 15, align = "center")), subtitle = list(gt::cell_text(weight = "bold", </span></span>
+<span><span class="co">#&gt;     size = 12, align = "center")), body = list())</span></span>
+<span></span>
+<span><span class="fu"><a href="../reference/tableStyle.html">tableStyle</a></span><span class="op">(</span>type <span class="op">=</span> <span class="st">"flextable"</span><span class="op">)</span></span>
+<span><span class="co">#&gt; list(header = list(cell = officer::fp_cell(background.color = "#c8c8c8"), </span></span>
+<span><span class="co">#&gt;     text = officer::fp_text(bold = TRUE)), header_name = list(cell = officer::fp_cell(background.color = "#d9d9d9"), </span></span>
+<span><span class="co">#&gt;     text = officer::fp_text(bold = TRUE)), header_level = list(cell = officer::fp_cell(background.color = "#e1e1e1"), </span></span>
+<span><span class="co">#&gt;     text = officer::fp_text(bold = TRUE)), column_name = list(text = officer::fp_text(bold = TRUE)), </span></span>
+<span><span class="co">#&gt;     group_label = list(cell = officer::fp_cell(background.color = "#e9e9e9", </span></span>
+<span><span class="co">#&gt;         border = officer::fp_border(color = "gray")), text = officer::fp_text(bold = TRUE)), </span></span>
+<span><span class="co">#&gt;     title = list(text = officer::fp_text(bold = TRUE, font.size = 15)), </span></span>
+<span><span class="co">#&gt;     subtitle = list(text = officer::fp_text(bold = TRUE, font.size = 12)), </span></span>
+<span><span class="co">#&gt;     body = list())</span></span>
+<span></span>
+<span><span class="fu"><a href="../reference/tableStyle.html">tableStyle</a></span><span class="op">(</span>type <span class="op">=</span> <span class="st">"datatable"</span><span class="op">)</span></span>
+<span><span class="co">#&gt; list(caption = "caption-side: bottom; text-align: center;", scrollX = TRUE, </span></span>
+<span><span class="co">#&gt;     scrollY = 400, scroller = TRUE, deferRender = TRUE, scrollCollapse = TRUE, </span></span>
+<span><span class="co">#&gt;     fixedColumns = list(leftColumns = 1, rightColumns = 1), fixedHeader = TRUE, </span></span>
+<span><span class="co">#&gt;     pageLength = 10, lengthMenu = c(5, 10, 20, 50, 100), filter = "bottom", </span></span>
+<span><span class="co">#&gt;     searchHighlight = TRUE, rownames = FALSE)</span></span></code></pre></div>
+</div>
+</div>
+</div>
+<div class="section level2">
+<h2 id="format-functions">
+<code>format</code> Functions<a class="anchor" aria-label="anchor" href="#format-functions"></a>
+</h2>
+<p>The <code>format</code> set of functions can be used in a pipeline to
+transform and format a <code>&lt;data.frame&gt;</code> or a
+<code>&lt;summarised_result&gt;</code> object. Below, we’ll demonstrate
+how to utilize these functions in a step-by-step manner.</p>
+<div class="section level3">
+<h3 id="format-estimates">1) Format Estimates<a class="anchor" aria-label="anchor" href="#format-estimates"></a>
+</h3>
+<p>The <code><a href="../reference/formatEstimateName.html">formatEstimateName()</a></code> and
+<code><a href="../reference/formatEstimateValue.html">formatEstimateValue()</a></code> functions enable you to customise the
+naming and display of estimates in your table.</p>
+<p>To illustrate their usage, we’ll continue with the
+<code>result</code> dataset. Let’s first take a look at some of the
+estimates before any formatting is applied:</p>
+<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="va">result</span> <span class="op">|&gt;</span> </span>
+<span>  <span class="fu"><a href="https://darwin-eu.github.io/omopgenerics/reference/filterGroup.html" class="external-link">filterGroup</a></span><span class="op">(</span><span class="va">cohort_name</span> <span class="op">==</span> <span class="st">"cohort1"</span><span class="op">)</span> <span class="op">|&gt;</span>  <span class="co"># visOmopResult filter function</span></span>
+<span>  <span class="fu"><a href="https://darwin-eu.github.io/omopgenerics/reference/filterStrata.html" class="external-link">filterStrata</a></span><span class="op">(</span><span class="va">age_group</span> <span class="op">==</span> <span class="st">"&lt;40"</span>, <span class="va">sex</span> <span class="op">==</span> <span class="st">"Female"</span><span class="op">)</span> <span class="op">|&gt;</span>  <span class="co"># visOmopResult filter function</span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">variable_name</span>, <span class="va">variable_level</span>, <span class="va">estimate_name</span>, <span class="va">estimate_type</span>, <span class="va">estimate_value</span><span class="op">)</span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 7 × 5</span></span></span>
+<span><span class="co">#&gt;   variable_name   variable_level estimate_name estimate_type estimate_value  </span></span>
+<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>           <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>          <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>           </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> number subjects <span style="color: #BB0000;">NA</span>             count         integer       1956698         </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> age             <span style="color: #BB0000;">NA</span>             mean          numeric       63.6465614894405</span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> age             <span style="color: #BB0000;">NA</span>             sd            numeric       3.15241752425209</span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> Medications     Amoxiciline    count         integer       27860           </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">5</span> Medications     Amoxiciline    percentage    percentage    21.3172711199149</span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">6</span> Medications     Ibuprofen      count         integer       66887           </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">7</span> Medications     Ibuprofen      percentage    percentage    91.8803214561194</span></span></code></pre></div>
+<div class="section level4">
+<h4 id="estimate-values">1.1) Estimate values<a class="anchor" aria-label="anchor" href="#estimate-values"></a>
+</h4>
+<p>The <code><a href="../reference/formatEstimateValue.html">formatEstimateValue()</a></code> function allows you to specify
+the number of decimals for different <code>estimate_types</code> or
+<code>estimate_names</code>, as well as customise decimal and thousand
+separators.</p>
+<p>Let’s see how the previous estimates are updated afterwars:</p>
+<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="co"># Formatting estimate values</span></span>
+<span><span class="va">result</span> <span class="op">&lt;-</span> <span class="va">result</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="../reference/formatEstimateValue.html">formatEstimateValue</a></span><span class="op">(</span></span>
+<span>    decimals <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>integer <span class="op">=</span> <span class="fl">0</span>, numeric <span class="op">=</span> <span class="fl">4</span>, percentage <span class="op">=</span> <span class="fl">2</span><span class="op">)</span>,</span>
+<span>    decimalMark <span class="op">=</span> <span class="st">"."</span>,</span>
+<span>    bigMark <span class="op">=</span> <span class="st">","</span></span>
+<span>  <span class="op">)</span></span>
+<span></span>
+<span><span class="co"># Displaying the formatted subset</span></span>
+<span><span class="va">result</span> <span class="op">|&gt;</span> </span>
+<span>  <span class="fu"><a href="https://darwin-eu.github.io/omopgenerics/reference/filterGroup.html" class="external-link">filterGroup</a></span><span class="op">(</span><span class="va">cohort_name</span> <span class="op">==</span> <span class="st">"cohort1"</span><span class="op">)</span> <span class="op">|&gt;</span>  </span>
+<span>  <span class="fu"><a href="https://darwin-eu.github.io/omopgenerics/reference/filterStrata.html" class="external-link">filterStrata</a></span><span class="op">(</span><span class="va">age_group</span> <span class="op">==</span> <span class="st">"&lt;40"</span>, <span class="va">sex</span> <span class="op">==</span> <span class="st">"Female"</span><span class="op">)</span> <span class="op">|&gt;</span> </span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">variable_name</span>, <span class="va">variable_level</span>, <span class="va">estimate_name</span>, <span class="va">estimate_type</span>, <span class="va">estimate_value</span><span class="op">)</span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 7 × 5</span></span></span>
+<span><span class="co">#&gt;   variable_name   variable_level estimate_name estimate_type estimate_value</span></span>
+<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>           <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>          <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> number subjects <span style="color: #BB0000;">NA</span>             count         integer       1,956,698     </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> age             <span style="color: #BB0000;">NA</span>             mean          numeric       63.6466       </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> age             <span style="color: #BB0000;">NA</span>             sd            numeric       3.1524        </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> Medications     Amoxiciline    count         integer       27,860        </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">5</span> Medications     Amoxiciline    percentage    percentage    21.32         </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">6</span> Medications     Ibuprofen      count         integer       66,887        </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">7</span> Medications     Ibuprofen      percentage    percentage    91.88</span></span></code></pre></div>
+<p>As you can see, the estimates now reflect the specified formatting
+rules.</p>
+</div>
+<div class="section level4">
+<h4 id="estimate-names">1.2) Estimate names<a class="anchor" aria-label="anchor" href="#estimate-names"></a>
+</h4>
+<p>Next, we will format the estimate names using the
+<code><a href="../reference/formatEstimateName.html">formatEstimateName()</a></code> function. This function allows us to
+combine counts and percentages as “N (%)”, among other estimate
+combinations</p>
+<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="co"># Formatting estimate names</span></span>
+<span><span class="va">result</span> <span class="op">&lt;-</span> <span class="va">result</span> <span class="op">|&gt;</span> </span>
+<span>  <span class="fu"><a href="../reference/formatEstimateName.html">formatEstimateName</a></span><span class="op">(</span></span>
+<span>    estimateName <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span></span>
+<span>      <span class="st">"N (%)"</span> <span class="op">=</span> <span class="st">"&lt;count&gt; (&lt;percentage&gt;%)"</span>, </span>
+<span>      <span class="st">"N"</span> <span class="op">=</span> <span class="st">"&lt;count&gt;"</span>,</span>
+<span>      <span class="st">"Mean (SD)"</span> <span class="op">=</span> <span class="st">"&lt;mean&gt; (&lt;sd&gt;)"</span></span>
+<span>    <span class="op">)</span>,</span>
+<span>    keepNotFormatted <span class="op">=</span> <span class="cn">TRUE</span>,</span>
+<span>    useFormatOrder <span class="op">=</span> <span class="cn">FALSE</span></span>
+<span>  <span class="op">)</span></span>
+<span></span>
+<span><span class="co"># Displaying the formatted subset with new estimate names</span></span>
+<span><span class="va">result</span> <span class="op">|&gt;</span> </span>
+<span>  <span class="fu"><a href="https://darwin-eu.github.io/omopgenerics/reference/filterGroup.html" class="external-link">filterGroup</a></span><span class="op">(</span><span class="va">cohort_name</span> <span class="op">==</span> <span class="st">"cohort1"</span><span class="op">)</span> <span class="op">|&gt;</span>  </span>
+<span>  <span class="fu"><a href="https://darwin-eu.github.io/omopgenerics/reference/filterStrata.html" class="external-link">filterStrata</a></span><span class="op">(</span><span class="va">age_group</span> <span class="op">==</span> <span class="st">"&lt;40"</span>, <span class="va">sex</span> <span class="op">==</span> <span class="st">"Female"</span><span class="op">)</span> <span class="op">|&gt;</span> </span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">variable_name</span>, <span class="va">variable_level</span>, <span class="va">estimate_name</span>, <span class="va">estimate_type</span>, <span class="va">estimate_value</span><span class="op">)</span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 4 × 5</span></span></span>
+<span><span class="co">#&gt;   variable_name   variable_level estimate_name estimate_type estimate_value  </span></span>
+<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>           <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>          <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>           </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> number subjects <span style="color: #BB0000;">NA</span>             N             character     1,956,698       </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> age             <span style="color: #BB0000;">NA</span>             Mean (SD)     character     63.6466 (3.1524)</span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> Medications     Amoxiciline    N (%)         character     27,860 (21.32%) </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> Medications     Ibuprofen      N (%)         character     66,887 (91.88%)</span></span></code></pre></div>
+<p>Now, the estimate names are displayed as specified, such as “N (%)”
+for counts and percentages. The <code>keepNotFormatted</code> argument
+ensures that unformatted rows remain in the dataset, while
+<code>useFormatOrder</code> allows control over the display order of the
+estimates.</p>
+</div>
+</div>
+<div class="section level3">
+<h3 id="format-header">2) Format Header<a class="anchor" aria-label="anchor" href="#format-header"></a>
+</h3>
+<p><code><a href="../reference/formatHeader.html">formatHeader()</a></code> is used to create complex multi-level
+headers for tables, making it easy to present grouped data clearly.</p>
+<div class="section level4">
+<h4 id="header-levels">Header levels<a class="anchor" aria-label="anchor" href="#header-levels"></a>
+</h4>
+<p>There are 3 different levels of headers, each identified with the
+following keys:</p>
+<ul>
+<li><p><code>header</code>: Custom labels that do not correspond to
+column names or table values.</p></li>
+<li><p><code>header_name</code>: Labels derived from column names. Can
+be omitted with <code>includeHeaderName =  FALSE</code>.</p></li>
+<li><p><code>header_level</code>: Labels derived from values within
+columns set in <code>header</code>.</p></li>
+</ul>
+<p>These keys, together with a delimiter between header levels
+(<code>delim</code>) are used in <code><a href="../reference/formatTable.html">formatTable()</a></code> to format
+and style <code>gt</code> or <code>flextable</code> tables.</p>
+<p>Let’s create a multi-level header for the strata columns, including
+all three keys. This will show how the column names are transformed:</p>
+<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="va">result</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"strata_name"</span>, <span class="st">"strata_level"</span><span class="op">)</span>, <span class="op">~</span> <span class="fu"><a href="https://rdrr.io/r/base/grep.html" class="external-link">gsub</a></span><span class="op">(</span><span class="st">"&amp;&amp;&amp;"</span>, <span class="st">"and"</span>, <span class="va">.x</span><span class="op">)</span><span class="op">)</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="../reference/formatHeader.html">formatHeader</a></span><span class="op">(</span></span>
+<span>    header <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Stratifications"</span>, <span class="st">"strata_name"</span>, <span class="st">"strata_level"</span><span class="op">)</span>,</span>
+<span>    delim <span class="op">=</span> <span class="st">"\n"</span>,</span>
+<span>    includeHeaderName <span class="op">=</span> <span class="cn">TRUE</span>,</span>
+<span>    includeHeaderKey <span class="op">=</span> <span class="cn">TRUE</span></span>
+<span>  <span class="op">)</span> <span class="op">|&gt;</span> </span>
+<span>  <span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">colnames</a></span><span class="op">(</span><span class="op">)</span></span>
+<span><span class="co">#&gt;  [1] "result_id"                                                                                                                                   </span></span>
+<span><span class="co">#&gt;  [2] "cdm_name"                                                                                                                                    </span></span>
+<span><span class="co">#&gt;  [3] "group_name"                                                                                                                                  </span></span>
+<span><span class="co">#&gt;  [4] "group_level"                                                                                                                                 </span></span>
+<span><span class="co">#&gt;  [5] "variable_name"                                                                                                                               </span></span>
+<span><span class="co">#&gt;  [6] "variable_level"                                                                                                                              </span></span>
+<span><span class="co">#&gt;  [7] "estimate_name"                                                                                                                               </span></span>
+<span><span class="co">#&gt;  [8] "estimate_type"                                                                                                                               </span></span>
+<span><span class="co">#&gt;  [9] "additional_name"                                                                                                                             </span></span>
+<span><span class="co">#&gt; [10] "additional_level"                                                                                                                            </span></span>
+<span><span class="co">#&gt; [11] "[header]Stratifications\n[header_name]strata_name\n[header_level]age_group and sex\n[header_name]strata_level\n[header_level]&lt;40 and Male"   </span></span>
+<span><span class="co">#&gt; [12] "[header]Stratifications\n[header_name]strata_name\n[header_level]age_group and sex\n[header_name]strata_level\n[header_level]&gt;=40 and Male"  </span></span>
+<span><span class="co">#&gt; [13] "[header]Stratifications\n[header_name]strata_name\n[header_level]age_group and sex\n[header_name]strata_level\n[header_level]&lt;40 and Female" </span></span>
+<span><span class="co">#&gt; [14] "[header]Stratifications\n[header_name]strata_name\n[header_level]age_group and sex\n[header_name]strata_level\n[header_level]&gt;=40 and Female"</span></span></code></pre></div>
+<p>For the table we are formatting, we won’t include the
+<code>header_name</code> labels. Let’s see how it looks when we exclude
+them:</p>
+<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="va">result</span> <span class="op">&lt;-</span> <span class="va">result</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html" class="external-link">across</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"strata_name"</span>, <span class="st">"strata_level"</span><span class="op">)</span>, <span class="op">~</span> <span class="fu"><a href="https://rdrr.io/r/base/grep.html" class="external-link">gsub</a></span><span class="op">(</span><span class="st">"&amp;&amp;&amp;"</span>, <span class="st">"and"</span>, <span class="va">.x</span><span class="op">)</span><span class="op">)</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="../reference/formatHeader.html">formatHeader</a></span><span class="op">(</span></span>
+<span>    header <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Stratifications"</span>, <span class="st">"strata_name"</span>, <span class="st">"strata_level"</span><span class="op">)</span>,</span>
+<span>    delim <span class="op">=</span> <span class="st">"\n"</span>,</span>
+<span>    includeHeaderName <span class="op">=</span> <span class="cn">FALSE</span>,</span>
+<span>    includeHeaderKey <span class="op">=</span> <span class="cn">TRUE</span></span>
+<span>  <span class="op">)</span>  </span>
+<span></span>
+<span><span class="fu"><a href="https://rdrr.io/r/base/colnames.html" class="external-link">colnames</a></span><span class="op">(</span><span class="va">result</span><span class="op">)</span></span>
+<span><span class="co">#&gt;  [1] "result_id"                                                                              </span></span>
+<span><span class="co">#&gt;  [2] "cdm_name"                                                                               </span></span>
+<span><span class="co">#&gt;  [3] "group_name"                                                                             </span></span>
+<span><span class="co">#&gt;  [4] "group_level"                                                                            </span></span>
+<span><span class="co">#&gt;  [5] "variable_name"                                                                          </span></span>
+<span><span class="co">#&gt;  [6] "variable_level"                                                                         </span></span>
+<span><span class="co">#&gt;  [7] "estimate_name"                                                                          </span></span>
+<span><span class="co">#&gt;  [8] "estimate_type"                                                                          </span></span>
+<span><span class="co">#&gt;  [9] "additional_name"                                                                        </span></span>
+<span><span class="co">#&gt; [10] "additional_level"                                                                       </span></span>
+<span><span class="co">#&gt; [11] "[header]Stratifications\n[header_level]age_group and sex\n[header_level]&lt;40 and Male"   </span></span>
+<span><span class="co">#&gt; [12] "[header]Stratifications\n[header_level]age_group and sex\n[header_level]&gt;=40 and Male"  </span></span>
+<span><span class="co">#&gt; [13] "[header]Stratifications\n[header_level]age_group and sex\n[header_level]&lt;40 and Female" </span></span>
+<span><span class="co">#&gt; [14] "[header]Stratifications\n[header_level]age_group and sex\n[header_level]&gt;=40 and Female"</span></span></code></pre></div>
+</div>
+</div>
+<div class="section level3">
+<h3 id="format-table">3) Format Table<a class="anchor" aria-label="anchor" href="#format-table"></a>
+</h3>
+<p><code><a href="../reference/formatTable.html">formatTable()</a></code> function is the final step in the
+formatting pipeline, where the formatted <code>&lt;data.frame&gt;</code>
+is converted to either a <code>&lt;gt&gt;</code> or
+<code>&lt;flextable&gt;</code>.</p>
+<div class="section level4">
+<h4 id="prepare-data">Prepare data<a class="anchor" aria-label="anchor" href="#prepare-data"></a>
+</h4>
+<p>Before using <code><a href="../reference/formatTable.html">formatTable()</a></code>, we’ll tidy the
+<code>&lt;data.frame&gt;</code> by splitting the group and additional
+name-level columns (see vignette on tidying
+<code>&lt;summarised_result&gt;</code>), and drop some unwanted
+columns:</p>
+<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="va">result</span> <span class="op">&lt;-</span> <span class="va">result</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://darwin-eu.github.io/omopgenerics/reference/splitGroup.html" class="external-link">splitGroup</a></span><span class="op">(</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://darwin-eu.github.io/omopgenerics/reference/splitAdditional.html" class="external-link">splitAdditional</a></span><span class="op">(</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="op">!</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"result_id"</span>, <span class="st">"estimate_type"</span>, <span class="st">"cdm_name"</span><span class="op">)</span><span class="op">)</span></span>
+<span><span class="fu"><a href="https://rdrr.io/r/utils/head.html" class="external-link">head</a></span><span class="op">(</span><span class="va">result</span><span class="op">)</span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># A tibble: 6 × 8</span></span></span>
+<span><span class="co">#&gt;   cohort_name variable_name  variable_level estimate_name [header]Stratificati…¹</span></span>
+<span><span class="co">#&gt;   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>       <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>          <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>          <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>         <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span>                 </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">1</span> cohort1     number subjec… <span style="color: #BB0000;">NA</span>             N             3,203,857             </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">2</span> cohort2     number subjec… <span style="color: #BB0000;">NA</span>             N             7,353,196             </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">3</span> cohort1     age            <span style="color: #BB0000;">NA</span>             Mean (SD)     22.5563 (3.8918)      </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">4</span> cohort2     age            <span style="color: #BB0000;">NA</span>             Mean (SD)     68.0163 (0.6522)      </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">5</span> cohort1     Medications    Amoxiciline    N (%)         54,248 (92.00%)       </span></span>
+<span><span class="co">#&gt; <span style="color: #BCBCBC;">6</span> cohort2     Medications    Amoxiciline    N (%)         37,697 (71.83%)       </span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># ℹ abbreviated name:</span></span></span>
+<span><span class="co">#&gt; <span style="color: #949494;">#   ¹​`[header]Stratifications\n[header_level]age_group and sex\n[header_level]&lt;40 and Male`</span></span></span>
+<span><span class="co">#&gt; <span style="color: #949494;"># ℹ 3 more variables:</span></span></span>
+<span><span class="co">#&gt; <span style="color: #949494;">#   `[header]Stratifications\n[header_level]age_group and sex\n[header_level]&gt;=40 and Male` &lt;chr&gt;,</span></span></span>
+<span><span class="co">#&gt; <span style="color: #949494;">#   `[header]Stratifications\n[header_level]age_group and sex\n[header_level]&lt;40 and Female` &lt;chr&gt;,</span></span></span>
+<span><span class="co">#&gt; <span style="color: #949494;">#   `[header]Stratifications\n[header_level]age_group and sex\n[header_level]&gt;=40 and Female` &lt;chr&gt;</span></span></span></code></pre></div>
+</div>
+<div class="section level4">
+<h4 id="use-formattable">Use <code>formatTable()</code><a class="anchor" aria-label="anchor" href="#use-formattable"></a>
+</h4>
+<p>Now that the data is cleaned and organized,
+<code><a href="../reference/formatTable.html">formatTable()</a></code> can be used to create a well-structured
+<code>&lt;gt&gt;</code> or <code>&lt;flextable&gt;</code> object.</p>
+<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="va">result</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="../reference/formatTable.html">formatTable</a></span><span class="op">(</span></span>
+<span>    type <span class="op">=</span> <span class="st">"gt"</span>,</span>
+<span>    delim <span class="op">=</span> <span class="st">"\n"</span>,</span>
+<span>    style <span class="op">=</span> <span class="st">"default"</span>,</span>
+<span>    na <span class="op">=</span> <span class="st">"-"</span>,</span>
+<span>    title <span class="op">=</span> <span class="st">"My formatted table!"</span>,</span>
+<span>    subtitle <span class="op">=</span> <span class="st">"Created with the `visOmopResults` R package."</span>,</span>
+<span>    caption <span class="op">=</span> <span class="cn">NULL</span>,</span>
+<span>    groupColumn <span class="op">=</span> <span class="st">"cohort_name"</span>,</span>
+<span>    groupAsColumn <span class="op">=</span> <span class="cn">FALSE</span>,</span>
+<span>    groupOrder <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"cohort2"</span>, <span class="st">"cohort1"</span><span class="op">)</span>,</span>
+<span>    merge <span class="op">=</span> <span class="st">"variable_name"</span></span>
+<span>  <span class="op">)</span></span></code></pre></div>
+<div id="lgkjhvqlto" style="padding-left:0px;padding-right:0px;padding-top:10px;padding-bottom:10px;overflow-x:auto;overflow-y:auto;width:auto;height:auto;">
+<style>#lgkjhvqlto table {
+  font-family: system-ui, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol', 'Noto Color Emoji';
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+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#lgkjhvqlto .gt_column_spanner_outer {
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+}
+
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+  padding-right: 5px;
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+  border-top-width: 2px;
+}
+
+#lgkjhvqlto .gt_last_summary_row {
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+  padding-bottom: 8px;
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+  border-bottom-width: 2px;
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+
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+  padding-left: 5px;
+  padding-right: 5px;
+}
+
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+  padding-bottom: 8px;
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+  padding-right: 5px;
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+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
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+
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+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#lgkjhvqlto .gt_footnotes {
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+  border-right-color: #D3D3D3;
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+#lgkjhvqlto .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#lgkjhvqlto .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
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+  border-right-color: #D3D3D3;
+}
+
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+  padding-top: 4px;
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+  padding-left: 5px;
+  padding-right: 5px;
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+
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+}
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+}
+
+#lgkjhvqlto .gt_font_bold {
+  font-weight: bold;
+}
+
+#lgkjhvqlto .gt_font_italic {
+  font-style: italic;
+}
+
+#lgkjhvqlto .gt_super {
+  font-size: 65%;
+}
+
+#lgkjhvqlto .gt_footnote_marks {
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+  vertical-align: 0.4em;
+  position: initial;
+}
+
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+  font-size: 100%;
+  vertical-align: 0;
+}
+
+#lgkjhvqlto .gt_indent_1 {
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+}
+
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+
+#lgkjhvqlto .gt_indent_3 {
+  text-indent: 15px;
+}
+
+#lgkjhvqlto .gt_indent_4 {
+  text-indent: 20px;
+}
+
+#lgkjhvqlto .gt_indent_5 {
+  text-indent: 25px;
+}
+
+#lgkjhvqlto .katex-display {
+  display: inline-flex !important;
+  margin-bottom: 0.75em !important;
+}
+
+#lgkjhvqlto div.Reactable > div.rt-table > div.rt-thead > div.rt-tr.rt-tr-group-header > div.rt-th-group:after {
+  height: 0px !important;
+}
+</style>
+<table class="table gt_table" data-quarto-disable-processing="false" data-quarto-bootstrap="false">
+<thead>
+<tr class="gt_heading">
+<td colspan="7" class="gt_heading gt_title gt_font_normal" style="font-size: 15; text-align: center; font-weight: bold;">My formatted table!</td>
+    </tr>
+<tr class="gt_heading">
+<td colspan="7" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style="font-size: 12; text-align: center; font-weight: bold;">Created with the `visOmopResults` R package.</td>
+    </tr>
+<tr class="gt_col_headings gt_spanner_row">
+<th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="3" style="background-color: #C8C8C8; text-align: center; font-weight: bold;" scope="colgroup"></th>
+      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="4" style="background-color: #C8C8C8; text-align: center; font-weight: bold;" scope="colgroup" id="spanner-[header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Male">
+        <div class="gt_column_spanner">Stratifications</div>
+      </th>
+    </tr>
+<tr class="gt_col_headings gt_spanner_row">
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1" style="text-align: center; font-weight: bold;" scope="col" id="variable_name">variable_name</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1" style="text-align: center; font-weight: bold;" scope="col" id="variable_level">variable_level</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1" style="text-align: center; font-weight: bold;" scope="col" id="estimate_name">estimate_name</th>
+      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="4" style="background-color: #E1E1E1; text-align: center; font-weight: bold;" scope="colgroup" id="spanner-[header_level]age_group and sex
+[header_level]&lt;40 and Male">
+        <div class="gt_column_spanner">age_group and sex</div>
+      </th>
+    </tr>
+<tr class="gt_col_headings">
+<th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1" style="background-color: #E1E1E1; text-align: center; font-weight: bold;" scope="col" id="[header]Stratifications-[header_level]age_group-and-sex-[header_level]&lt;40-and-Male">&lt;40 and Male</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1" style="background-color: #E1E1E1; text-align: center; font-weight: bold;" scope="col" id="[header]Stratifications-[header_level]age_group-and-sex-[header_level]&gt;=40-and-Male">&gt;=40 and Male</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1" style="background-color: #E1E1E1; text-align: center; font-weight: bold;" scope="col" id="[header]Stratifications-[header_level]age_group-and-sex-[header_level]&lt;40-and-Female">&lt;40 and Female</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1" style="background-color: #E1E1E1; text-align: center; font-weight: bold;" scope="col" id="[header]Stratifications-[header_level]age_group-and-sex-[header_level]&gt;=40-and-Female">&gt;=40 and Female</th>
+    </tr>
+</thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<th colspan="7" class="gt_group_heading" style="background-color: #E9E9E9; font-weight: bold;" scope="colgroup" id="cohort2">cohort2</th>
+    </tr>
+<tr class="gt_row_group_first">
+<td headers="cohort2  variable_name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">number subjects</td>
+<td headers="cohort2  variable_level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="cohort2  estimate_name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Male" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">7,353,196</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Male" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">1,959,567</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Female" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">9,805,397</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Female" class="gt_row gt_right" style="text-align: right;">7,415,215</td>
+</tr>
+<tr>
+<td headers="cohort2  variable_name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">age</td>
+<td headers="cohort2  variable_level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="cohort2  estimate_name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Mean (SD)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Male" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">68.0163 (0.6522)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Male" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">49.8846 (3.5421)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Female" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">64.1679 (8.2520)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Female" class="gt_row gt_right" style="text-align: right;">66.0284 (2.7382)</td>
+</tr>
+<tr>
+<td headers="cohort2  variable_name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Medications</td>
+<td headers="cohort2  variable_level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Amoxiciline</td>
+<td headers="cohort2  estimate_name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N (%)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Male" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">37,697 (71.83%)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Male" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">55,991 (24.13%)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Female" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">85,708 (54.70%)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Female" class="gt_row gt_right" style="text-align: right;">38,481 (83.48%)</td>
+</tr>
+<tr>
+<td headers="cohort2  variable_name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="cohort2  variable_level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Ibuprofen</td>
+<td headers="cohort2  estimate_name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N (%)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Male" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">1,148 (16.46%)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Male" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">88,825 (66.32%)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Female" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">99,635 (85.66%)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Female" class="gt_row gt_right" style="text-align: right;">50,019 (92.65%)</td>
+</tr>
+<tr class="gt_group_heading_row">
+<th colspan="7" class="gt_group_heading" style="background-color: #E9E9E9; font-weight: bold;" scope="colgroup" id="cohort1">cohort1</th>
+    </tr>
+<tr class="gt_row_group_first">
+<td headers="cohort1  variable_name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">number subjects</td>
+<td headers="cohort1  variable_level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="cohort1  estimate_name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Male" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">3,203,857</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Male" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">4,023,282</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Female" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">1,956,698</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Female" class="gt_row gt_right" style="text-align: right;">4,035,381</td>
+</tr>
+<tr>
+<td headers="cohort1  variable_name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">age</td>
+<td headers="cohort1  variable_level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="cohort1  estimate_name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Mean (SD)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Male" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">22.5563 (3.8918)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Male" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">30.0831 (4.6119)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Female" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">63.6466 (3.1524)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Female" class="gt_row gt_right" style="text-align: right;">47.9025 (1.7468)</td>
+</tr>
+<tr>
+<td headers="cohort1  variable_name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Medications</td>
+<td headers="cohort1  variable_level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Amoxiciline</td>
+<td headers="cohort1  estimate_name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N (%)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Male" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">54,248 (92.00%)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Male" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">54,460 (40.07%)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Female" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">27,860 (21.32%)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Female" class="gt_row gt_right" style="text-align: right;">44,670 (67.18%)</td>
+</tr>
+<tr>
+<td headers="cohort1  variable_name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="cohort1  variable_level" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Ibuprofen</td>
+<td headers="cohort1  estimate_name" class="gt_row gt_left" style="text-align: left; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N (%)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Male" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">21,843 (56.69%)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Male" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">41,836 (25.30%)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Female" class="gt_row gt_right" style="text-align: right; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">66,887 (91.88%)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Female" class="gt_row gt_right" style="text-align: right;">50,765 (86.74%)</td>
+</tr>
+</tbody>
+</table>
+</div>
+<p>In the examples above, we used the default style defined in the
+<em>visOmopResults</em> package (use <code>gtStyle()</code> and
+<code>flextableStyle()</code> to see these styles). However, it’s
+possible to customise the appearance of different parts of the table to
+better suit your needs.</p>
+</div>
+<div class="section level4">
+<h4 id="customising-table-styles">customising Table Styles<a class="anchor" aria-label="anchor" href="#customising-table-styles"></a>
+</h4>
+<p>Let’s start by applying a custom style to a <code>&lt;gt&gt;</code>
+table:</p>
+<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="va">result</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="../reference/formatTable.html">formatTable</a></span><span class="op">(</span></span>
+<span>    type <span class="op">=</span> <span class="st">"gt"</span>,</span>
+<span>    delim <span class="op">=</span> <span class="st">"\n"</span>,</span>
+<span>    style <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span>
+<span>      <span class="st">"header"</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="fu">gt</span><span class="fu">::</span><span class="fu"><a href="https://gt.rstudio.com/reference/cell_text.html" class="external-link">cell_text</a></span><span class="op">(</span>weight <span class="op">=</span> <span class="st">"bold"</span><span class="op">)</span>, </span>
+<span>                      <span class="fu">gt</span><span class="fu">::</span><span class="fu"><a href="https://gt.rstudio.com/reference/cell_fill.html" class="external-link">cell_fill</a></span><span class="op">(</span>color <span class="op">=</span> <span class="st">"orange"</span><span class="op">)</span><span class="op">)</span>,</span>
+<span>      <span class="st">"header_level"</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="fu">gt</span><span class="fu">::</span><span class="fu"><a href="https://gt.rstudio.com/reference/cell_text.html" class="external-link">cell_text</a></span><span class="op">(</span>weight <span class="op">=</span> <span class="st">"bold"</span><span class="op">)</span>, </span>
+<span>                      <span class="fu">gt</span><span class="fu">::</span><span class="fu"><a href="https://gt.rstudio.com/reference/cell_fill.html" class="external-link">cell_fill</a></span><span class="op">(</span>color <span class="op">=</span> <span class="st">"yellow"</span><span class="op">)</span><span class="op">)</span>,</span>
+<span>      <span class="st">"column_name"</span> <span class="op">=</span> <span class="fu">gt</span><span class="fu">::</span><span class="fu"><a href="https://gt.rstudio.com/reference/cell_text.html" class="external-link">cell_text</a></span><span class="op">(</span>weight <span class="op">=</span> <span class="st">"bold"</span><span class="op">)</span>,</span>
+<span>      <span class="st">"group_label"</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="fu">gt</span><span class="fu">::</span><span class="fu"><a href="https://gt.rstudio.com/reference/cell_fill.html" class="external-link">cell_fill</a></span><span class="op">(</span>color <span class="op">=</span> <span class="st">"blue"</span><span class="op">)</span>,</span>
+<span>                           <span class="fu">gt</span><span class="fu">::</span><span class="fu"><a href="https://gt.rstudio.com/reference/cell_text.html" class="external-link">cell_text</a></span><span class="op">(</span>color <span class="op">=</span> <span class="st">"white"</span>, weight <span class="op">=</span> <span class="st">"bold"</span><span class="op">)</span><span class="op">)</span>,</span>
+<span>      <span class="st">"title"</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="fu">gt</span><span class="fu">::</span><span class="fu"><a href="https://gt.rstudio.com/reference/cell_text.html" class="external-link">cell_text</a></span><span class="op">(</span>size <span class="op">=</span> <span class="fl">20</span>, weight <span class="op">=</span> <span class="st">"bold"</span><span class="op">)</span><span class="op">)</span>,</span>
+<span>      <span class="st">"subtitle"</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="fu">gt</span><span class="fu">::</span><span class="fu"><a href="https://gt.rstudio.com/reference/cell_text.html" class="external-link">cell_text</a></span><span class="op">(</span>size <span class="op">=</span> <span class="fl">15</span><span class="op">)</span><span class="op">)</span>,</span>
+<span>      <span class="st">"body"</span> <span class="op">=</span> <span class="fu">gt</span><span class="fu">::</span><span class="fu"><a href="https://gt.rstudio.com/reference/cell_text.html" class="external-link">cell_text</a></span><span class="op">(</span>color <span class="op">=</span> <span class="st">"red"</span><span class="op">)</span></span>
+<span>    <span class="op">)</span>,</span>
+<span>    na <span class="op">=</span> <span class="st">"-"</span>,</span>
+<span>    title <span class="op">=</span> <span class="st">"My formatted table!"</span>,</span>
+<span>    subtitle <span class="op">=</span> <span class="st">"Created with the `visOmopResults` R package."</span>,</span>
+<span>    caption <span class="op">=</span> <span class="cn">NULL</span>,</span>
+<span>    groupColumn <span class="op">=</span> <span class="st">"cohort_name"</span>,</span>
+<span>    groupAsColumn <span class="op">=</span> <span class="cn">FALSE</span>,</span>
+<span>    groupOrder <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"cohort2"</span>, <span class="st">"cohort1"</span><span class="op">)</span>,</span>
+<span>    merge <span class="op">=</span> <span class="st">"variable_name"</span></span>
+<span>  <span class="op">)</span></span></code></pre></div>
+<div id="rlvuzjcdmf" style="padding-left:0px;padding-right:0px;padding-top:10px;padding-bottom:10px;overflow-x:auto;overflow-y:auto;width:auto;height:auto;">
+<style>#rlvuzjcdmf table {
+  font-family: system-ui, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol', 'Noto Color Emoji';
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+}
+
+#rlvuzjcdmf thead, #rlvuzjcdmf tbody, #rlvuzjcdmf tfoot, #rlvuzjcdmf tr, #rlvuzjcdmf td, #rlvuzjcdmf th {
+  border-style: none;
+}
+
+#rlvuzjcdmf p {
+  margin: 0;
+  padding: 0;
+}
+
+#rlvuzjcdmf .gt_table {
+  display: table;
+  border-collapse: collapse;
+  line-height: normal;
+  margin-left: auto;
+  margin-right: auto;
+  color: #333333;
+  font-size: 16px;
+  font-weight: normal;
+  font-style: normal;
+  background-color: #FFFFFF;
+  width: auto;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #A8A8A8;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #A8A8A8;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+}
+
+#rlvuzjcdmf .gt_caption {
+  padding-top: 4px;
+  padding-bottom: 4px;
+}
+
+#rlvuzjcdmf .gt_title {
+  color: #333333;
+  font-size: 125%;
+  font-weight: initial;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-bottom-color: #FFFFFF;
+  border-bottom-width: 0;
+}
+
+#rlvuzjcdmf .gt_subtitle {
+  color: #333333;
+  font-size: 85%;
+  font-weight: initial;
+  padding-top: 3px;
+  padding-bottom: 5px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-color: #FFFFFF;
+  border-top-width: 0;
+}
+
+#rlvuzjcdmf .gt_heading {
+  background-color: #FFFFFF;
+  text-align: center;
+  border-bottom-color: #FFFFFF;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#rlvuzjcdmf .gt_bottom_border {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#rlvuzjcdmf .gt_col_headings {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+}
+
+#rlvuzjcdmf .gt_col_heading {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 6px;
+  padding-left: 5px;
+  padding-right: 5px;
+  overflow-x: hidden;
+}
+
+#rlvuzjcdmf .gt_column_spanner_outer {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: normal;
+  text-transform: inherit;
+  padding-top: 0;
+  padding-bottom: 0;
+  padding-left: 4px;
+  padding-right: 4px;
+}
+
+#rlvuzjcdmf .gt_column_spanner_outer:first-child {
+  padding-left: 0;
+}
+
+#rlvuzjcdmf .gt_column_spanner_outer:last-child {
+  padding-right: 0;
+}
+
+#rlvuzjcdmf .gt_column_spanner {
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: bottom;
+  padding-top: 5px;
+  padding-bottom: 5px;
+  overflow-x: hidden;
+  display: inline-block;
+  width: 100%;
+}
+
+#rlvuzjcdmf .gt_spanner_row {
+  border-bottom-style: hidden;
+}
+
+#rlvuzjcdmf .gt_group_heading {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  text-align: left;
+}
+
+#rlvuzjcdmf .gt_empty_group_heading {
+  padding: 0.5px;
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  vertical-align: middle;
+}
+
+#rlvuzjcdmf .gt_from_md > :first-child {
+  margin-top: 0;
+}
+
+#rlvuzjcdmf .gt_from_md > :last-child {
+  margin-bottom: 0;
+}
+
+#rlvuzjcdmf .gt_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  margin: 10px;
+  border-top-style: solid;
+  border-top-width: 1px;
+  border-top-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 1px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 1px;
+  border-right-color: #D3D3D3;
+  vertical-align: middle;
+  overflow-x: hidden;
+}
+
+#rlvuzjcdmf .gt_stub {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#rlvuzjcdmf .gt_stub_row_group {
+  color: #333333;
+  background-color: #FFFFFF;
+  font-size: 100%;
+  font-weight: initial;
+  text-transform: inherit;
+  border-right-style: solid;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+  padding-left: 5px;
+  padding-right: 5px;
+  vertical-align: top;
+}
+
+#rlvuzjcdmf .gt_row_group_first td {
+  border-top-width: 2px;
+}
+
+#rlvuzjcdmf .gt_row_group_first th {
+  border-top-width: 2px;
+}
+
+#rlvuzjcdmf .gt_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#rlvuzjcdmf .gt_first_summary_row {
+  border-top-style: solid;
+  border-top-color: #D3D3D3;
+}
+
+#rlvuzjcdmf .gt_first_summary_row.thick {
+  border-top-width: 2px;
+}
+
+#rlvuzjcdmf .gt_last_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#rlvuzjcdmf .gt_grand_summary_row {
+  color: #333333;
+  background-color: #FFFFFF;
+  text-transform: inherit;
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#rlvuzjcdmf .gt_first_grand_summary_row {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-top-style: double;
+  border-top-width: 6px;
+  border-top-color: #D3D3D3;
+}
+
+#rlvuzjcdmf .gt_last_grand_summary_row_top {
+  padding-top: 8px;
+  padding-bottom: 8px;
+  padding-left: 5px;
+  padding-right: 5px;
+  border-bottom-style: double;
+  border-bottom-width: 6px;
+  border-bottom-color: #D3D3D3;
+}
+
+#rlvuzjcdmf .gt_striped {
+  background-color: rgba(128, 128, 128, 0.05);
+}
+
+#rlvuzjcdmf .gt_table_body {
+  border-top-style: solid;
+  border-top-width: 2px;
+  border-top-color: #D3D3D3;
+  border-bottom-style: solid;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+}
+
+#rlvuzjcdmf .gt_footnotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#rlvuzjcdmf .gt_footnote {
+  margin: 0px;
+  font-size: 90%;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#rlvuzjcdmf .gt_sourcenotes {
+  color: #333333;
+  background-color: #FFFFFF;
+  border-bottom-style: none;
+  border-bottom-width: 2px;
+  border-bottom-color: #D3D3D3;
+  border-left-style: none;
+  border-left-width: 2px;
+  border-left-color: #D3D3D3;
+  border-right-style: none;
+  border-right-width: 2px;
+  border-right-color: #D3D3D3;
+}
+
+#rlvuzjcdmf .gt_sourcenote {
+  font-size: 90%;
+  padding-top: 4px;
+  padding-bottom: 4px;
+  padding-left: 5px;
+  padding-right: 5px;
+}
+
+#rlvuzjcdmf .gt_left {
+  text-align: left;
+}
+
+#rlvuzjcdmf .gt_center {
+  text-align: center;
+}
+
+#rlvuzjcdmf .gt_right {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+#rlvuzjcdmf .gt_font_normal {
+  font-weight: normal;
+}
+
+#rlvuzjcdmf .gt_font_bold {
+  font-weight: bold;
+}
+
+#rlvuzjcdmf .gt_font_italic {
+  font-style: italic;
+}
+
+#rlvuzjcdmf .gt_super {
+  font-size: 65%;
+}
+
+#rlvuzjcdmf .gt_footnote_marks {
+  font-size: 75%;
+  vertical-align: 0.4em;
+  position: initial;
+}
+
+#rlvuzjcdmf .gt_asterisk {
+  font-size: 100%;
+  vertical-align: 0;
+}
+
+#rlvuzjcdmf .gt_indent_1 {
+  text-indent: 5px;
+}
+
+#rlvuzjcdmf .gt_indent_2 {
+  text-indent: 10px;
+}
+
+#rlvuzjcdmf .gt_indent_3 {
+  text-indent: 15px;
+}
+
+#rlvuzjcdmf .gt_indent_4 {
+  text-indent: 20px;
+}
+
+#rlvuzjcdmf .gt_indent_5 {
+  text-indent: 25px;
+}
+
+#rlvuzjcdmf .katex-display {
+  display: inline-flex !important;
+  margin-bottom: 0.75em !important;
+}
+
+#rlvuzjcdmf div.Reactable > div.rt-table > div.rt-thead > div.rt-tr.rt-tr-group-header > div.rt-th-group:after {
+  height: 0px !important;
+}
+</style>
+<table class="table gt_table" data-quarto-disable-processing="false" data-quarto-bootstrap="false">
+<thead>
+<tr class="gt_heading">
+<td colspan="7" class="gt_heading gt_title gt_font_normal" style="font-size: 20; font-weight: bold;">My formatted table!</td>
+    </tr>
+<tr class="gt_heading">
+<td colspan="7" class="gt_heading gt_subtitle gt_font_normal gt_bottom_border" style="font-size: 15;">Created with the `visOmopResults` R package.</td>
+    </tr>
+<tr class="gt_col_headings gt_spanner_row">
+<th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="3" style="font-weight: bold; background-color: #FFA500;" scope="colgroup"></th>
+      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="4" style="font-weight: bold; background-color: #FFA500;" scope="colgroup" id="spanner-[header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Male">
+        <div class="gt_column_spanner">Stratifications</div>
+      </th>
+    </tr>
+<tr class="gt_col_headings gt_spanner_row">
+<th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1" style="font-weight: bold;" scope="col" id="variable_name">variable_name</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1" style="font-weight: bold;" scope="col" id="variable_level">variable_level</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_left" rowspan="2" colspan="1" style="font-weight: bold;" scope="col" id="estimate_name">estimate_name</th>
+      <th class="gt_center gt_columns_top_border gt_column_spanner_outer" rowspan="1" colspan="4" style="font-weight: bold; background-color: #FFFF00;" scope="colgroup" id="spanner-[header_level]age_group and sex
+[header_level]&lt;40 and Male">
+        <div class="gt_column_spanner">age_group and sex</div>
+      </th>
+    </tr>
+<tr class="gt_col_headings">
+<th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1" style="font-weight: bold; background-color: #FFFF00;" scope="col" id="[header]Stratifications-[header_level]age_group-and-sex-[header_level]&lt;40-and-Male">&lt;40 and Male</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1" style="font-weight: bold; background-color: #FFFF00;" scope="col" id="[header]Stratifications-[header_level]age_group-and-sex-[header_level]&gt;=40-and-Male">&gt;=40 and Male</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1" style="font-weight: bold; background-color: #FFFF00;" scope="col" id="[header]Stratifications-[header_level]age_group-and-sex-[header_level]&lt;40-and-Female">&lt;40 and Female</th>
+      <th class="gt_col_heading gt_columns_bottom_border gt_right" rowspan="1" colspan="1" style="font-weight: bold; background-color: #FFFF00;" scope="col" id="[header]Stratifications-[header_level]age_group-and-sex-[header_level]&gt;=40-and-Female">&gt;=40 and Female</th>
+    </tr>
+</thead>
+<tbody class="gt_table_body">
+<tr class="gt_group_heading_row">
+<th colspan="7" class="gt_group_heading" style="background-color: #0000FF; color: #FFFFFF; font-weight: bold;" scope="colgroup" id="cohort2">cohort2</th>
+    </tr>
+<tr class="gt_row_group_first">
+<td headers="cohort2  variable_name" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">number subjects</td>
+<td headers="cohort2  variable_level" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="cohort2  estimate_name" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Male" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">7,353,196</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Male" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">1,959,567</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Female" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">9,805,397</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Female" class="gt_row gt_right" style="text-align: right; color: #FF0000;">7,415,215</td>
+</tr>
+<tr>
+<td headers="cohort2  variable_name" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">age</td>
+<td headers="cohort2  variable_level" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="cohort2  estimate_name" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Mean (SD)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Male" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">68.0163 (0.6522)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Male" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">49.8846 (3.5421)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Female" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">64.1679 (8.2520)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Female" class="gt_row gt_right" style="text-align: right; color: #FF0000;">66.0284 (2.7382)</td>
+</tr>
+<tr>
+<td headers="cohort2  variable_name" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Medications</td>
+<td headers="cohort2  variable_level" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Amoxiciline</td>
+<td headers="cohort2  estimate_name" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N (%)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Male" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">37,697 (71.83%)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Male" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">55,991 (24.13%)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Female" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">85,708 (54.70%)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Female" class="gt_row gt_right" style="text-align: right; color: #FF0000;">38,481 (83.48%)</td>
+</tr>
+<tr>
+<td headers="cohort2  variable_name" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="cohort2  variable_level" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Ibuprofen</td>
+<td headers="cohort2  estimate_name" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N (%)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Male" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">1,148 (16.46%)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Male" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">88,825 (66.32%)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Female" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">99,635 (85.66%)</td>
+<td headers="cohort2  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Female" class="gt_row gt_right" style="text-align: right; color: #FF0000;">50,019 (92.65%)</td>
+</tr>
+<tr class="gt_group_heading_row">
+<th colspan="7" class="gt_group_heading" style="background-color: #0000FF; color: #FFFFFF; font-weight: bold;" scope="colgroup" id="cohort1">cohort1</th>
+    </tr>
+<tr class="gt_row_group_first">
+<td headers="cohort1  variable_name" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">number subjects</td>
+<td headers="cohort1  variable_level" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="cohort1  estimate_name" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Male" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">3,203,857</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Male" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">4,023,282</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Female" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">1,956,698</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Female" class="gt_row gt_right" style="text-align: right; color: #FF0000;">4,035,381</td>
+</tr>
+<tr>
+<td headers="cohort1  variable_name" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">age</td>
+<td headers="cohort1  variable_level" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">-</td>
+<td headers="cohort1  estimate_name" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Mean (SD)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Male" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">22.5563 (3.8918)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Male" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">30.0831 (4.6119)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Female" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">63.6466 (3.1524)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Female" class="gt_row gt_right" style="text-align: right; color: #FF0000;">47.9025 (1.7468)</td>
+</tr>
+<tr>
+<td headers="cohort1  variable_name" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Medications</td>
+<td headers="cohort1  variable_level" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Amoxiciline</td>
+<td headers="cohort1  estimate_name" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N (%)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Male" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">54,248 (92.00%)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Male" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">54,460 (40.07%)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Female" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">27,860 (21.32%)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Female" class="gt_row gt_right" style="text-align: right; color: #FF0000;">44,670 (67.18%)</td>
+</tr>
+<tr>
+<td headers="cohort1  variable_name" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: hidden; border-top-color: #000000; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;"></td>
+<td headers="cohort1  variable_level" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">Ibuprofen</td>
+<td headers="cohort1  estimate_name" class="gt_row gt_left" style="text-align: left; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">N (%)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Male" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">21,843 (56.69%)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Male" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">41,836 (25.30%)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&lt;40 and Female" class="gt_row gt_right" style="text-align: right; color: #FF0000; border-left-width: 1px; border-left-style: solid; border-left-color: #D3D3D3; border-right-width: 1px; border-right-style: solid; border-right-color: #D3D3D3; border-top-width: 1px; border-top-style: solid; border-top-color: #D3D3D3; border-bottom-width: 1px; border-bottom-style: solid; border-bottom-color: #D3D3D3;">66,887 (91.88%)</td>
+<td headers="cohort1  [header]Stratifications
+[header_level]age_group and sex
+[header_level]&gt;=40 and Female" class="gt_row gt_right" style="text-align: right; color: #FF0000;">50,765 (86.74%)</td>
+</tr>
+</tbody>
+</table>
+</div>
+<p>For creating a similarly styled <code>&lt;flextable&gt;</code>, the
+<a href="https://CRAN.R-project.org/package=officer" class="external-link"><code>office</code></a>
+R package is required to access specific formatting functions.</p>
+<div class="sourceCode" id="cb16"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="va">result</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="../reference/formatTable.html">formatTable</a></span><span class="op">(</span></span>
+<span>    type <span class="op">=</span> <span class="st">"flextable"</span>,</span>
+<span>    delim <span class="op">=</span> <span class="st">"\n"</span>,</span>
+<span>    style <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span>
+<span>      <span class="st">"header"</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span>
+<span>        <span class="st">"cell"</span> <span class="op">=</span> <span class="fu">officer</span><span class="fu">::</span><span class="fu"><a href="https://davidgohel.github.io/officer/reference/fp_cell.html" class="external-link">fp_cell</a></span><span class="op">(</span>background.color <span class="op">=</span> <span class="st">"orange"</span><span class="op">)</span>,</span>
+<span>        <span class="st">"text"</span> <span class="op">=</span> <span class="fu">officer</span><span class="fu">::</span><span class="fu"><a href="https://davidgohel.github.io/officer/reference/fp_text.html" class="external-link">fp_text</a></span><span class="op">(</span>bold <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span><span class="op">)</span>,</span>
+<span>      <span class="st">"header_level"</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span>
+<span>        <span class="st">"cell"</span> <span class="op">=</span> <span class="fu">officer</span><span class="fu">::</span><span class="fu"><a href="https://davidgohel.github.io/officer/reference/fp_cell.html" class="external-link">fp_cell</a></span><span class="op">(</span>background.color <span class="op">=</span> <span class="st">"yellow"</span><span class="op">)</span>,</span>
+<span>        <span class="st">"text"</span> <span class="op">=</span> <span class="fu">officer</span><span class="fu">::</span><span class="fu"><a href="https://davidgohel.github.io/officer/reference/fp_text.html" class="external-link">fp_text</a></span><span class="op">(</span>bold <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span><span class="op">)</span>,</span>
+<span>      <span class="st">"column_name"</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"text"</span> <span class="op">=</span> <span class="fu">officer</span><span class="fu">::</span><span class="fu"><a href="https://davidgohel.github.io/officer/reference/fp_text.html" class="external-link">fp_text</a></span><span class="op">(</span>bold <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span><span class="op">)</span>,</span>
+<span>      <span class="st">"group_label"</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span></span>
+<span>        <span class="st">"cell"</span> <span class="op">=</span> <span class="fu">officer</span><span class="fu">::</span><span class="fu"><a href="https://davidgohel.github.io/officer/reference/fp_cell.html" class="external-link">fp_cell</a></span><span class="op">(</span>background.color <span class="op">=</span> <span class="st">"blue"</span><span class="op">)</span>,</span>
+<span>        <span class="st">"text"</span> <span class="op">=</span> <span class="fu">officer</span><span class="fu">::</span><span class="fu"><a href="https://davidgohel.github.io/officer/reference/fp_text.html" class="external-link">fp_text</a></span><span class="op">(</span>bold <span class="op">=</span> <span class="cn">TRUE</span>, color <span class="op">=</span> <span class="st">"white"</span><span class="op">)</span><span class="op">)</span>,</span>
+<span>      <span class="st">"title"</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"text"</span> <span class="op">=</span> <span class="fu">officer</span><span class="fu">::</span><span class="fu"><a href="https://davidgohel.github.io/officer/reference/fp_text.html" class="external-link">fp_text</a></span><span class="op">(</span>bold <span class="op">=</span> <span class="cn">TRUE</span>, font.size <span class="op">=</span> <span class="fl">20</span><span class="op">)</span><span class="op">)</span>,</span>
+<span>      <span class="st">"subtitle"</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"text"</span> <span class="op">=</span> <span class="fu">officer</span><span class="fu">::</span><span class="fu"><a href="https://davidgohel.github.io/officer/reference/fp_text.html" class="external-link">fp_text</a></span><span class="op">(</span>font.size <span class="op">=</span> <span class="fl">15</span><span class="op">)</span><span class="op">)</span>,</span>
+<span>      <span class="st">"body"</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"text"</span> <span class="op">=</span> <span class="fu">officer</span><span class="fu">::</span><span class="fu"><a href="https://davidgohel.github.io/officer/reference/fp_text.html" class="external-link">fp_text</a></span><span class="op">(</span>color <span class="op">=</span> <span class="st">"red"</span><span class="op">)</span><span class="op">)</span></span>
+<span>    <span class="op">)</span>,</span>
+<span>    na <span class="op">=</span> <span class="st">"-"</span>,</span>
+<span>    title <span class="op">=</span> <span class="st">"My formatted table!"</span>,</span>
+<span>    subtitle <span class="op">=</span> <span class="st">"Created with the `visOmopResults` R package."</span>,</span>
+<span>    caption <span class="op">=</span> <span class="cn">NULL</span>,</span>
+<span>    groupColumn <span class="op">=</span> <span class="st">"cohort_name"</span>,</span>
+<span>    groupAsColumn <span class="op">=</span> <span class="cn">FALSE</span>,</span>
+<span>    groupOrder <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"cohort2"</span>, <span class="st">"cohort1"</span><span class="op">)</span>,</span>
+<span>    merge <span class="op">=</span> <span class="st">"variable_name"</span></span>
+<span>  <span class="op">)</span></span></code></pre></div>
+<div class="tabwid">
+<style>.cl-35e7f2ba{}.cl-35e19050{font-family:'Arial';font-size:20pt;font-weight:bold;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-35e1905a{font-family:'Arial';font-size:15pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-35e19064{font-family:'Arial';font-size:10pt;font-weight:bold;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-35e1906e{font-family:'Arial';font-size:10pt;font-weight:bold;font-style:normal;text-decoration:none;color:rgba(255, 255, 255, 1.00);background-color:transparent;}.cl-35e1906f{font-family:'Arial';font-size:10pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(255, 0, 0, 1.00);background-color:transparent;}.cl-35e40240{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-35e4024a{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-35e40254{margin:0;text-align:right;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-35e420d6{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.2pt solid rgba(190, 190, 190, 1.00);border-top: 1.2pt solid rgba(190, 190, 190, 1.00);border-left: 1.2pt solid rgba(190, 190, 190, 1.00);border-right: 1.2pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-35e420e0{width:0.75in;background-color:rgba(255, 165, 0, 1.00);vertical-align: middle;border-bottom: 1.2pt solid rgba(190, 190, 190, 1.00);border-top: 1.2pt solid rgba(190, 190, 190, 1.00);border-left: 1.2pt solid rgba(190, 190, 190, 1.00);border-right: 1.2pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-35e420e1{width:0.75in;background-color:rgba(255, 255, 0, 1.00);vertical-align: middle;border-bottom: 1.2pt solid rgba(190, 190, 190, 1.00);border-top: 1.2pt solid rgba(190, 190, 190, 1.00);border-left: 1.2pt solid rgba(190, 190, 190, 1.00);border-right: 1.2pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-35e420e2{width:0.75in;background-color:rgba(0, 0, 255, 1.00);vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-35e420ea{width:0.75in;background-color:rgba(0, 0, 255, 1.00);vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-35e420eb{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 1pt solid rgba(190, 190, 190, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-35e420ec{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-35e420f4{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-35e420f5{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-35e420f6{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1pt solid rgba(190, 190, 190, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 1pt solid rgba(190, 190, 190, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-35e420fe{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1pt solid rgba(190, 190, 190, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-35e420ff{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1pt solid rgba(190, 190, 190, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-35e42100{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1pt solid rgba(190, 190, 190, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}</style>
+<table data-quarto-disable-processing="true" class="table cl-35e7f2ba">
+<thead>
+<tr style="overflow-wrap:break-word;"><th colspan="8" class="cl-35e420d6"><p class="cl-35e40240"><span class="cl-35e19050">My formatted table!</span></p></th></tr>
+<tr style="overflow-wrap:break-word;"><th colspan="8" class="cl-35e420d6"><p class="cl-35e40240"><span class="cl-35e1905a">Created with the `visOmopResults` R package.</span></p></th></tr>
+<tr style="overflow-wrap:break-word;">
+<th rowspan="3" class="cl-35e420d6"><p class="cl-35e40240"><span class="cl-35e19064">cohort_name</span></p></th>
+<th rowspan="3" class="cl-35e420d6"><p class="cl-35e40240"><span class="cl-35e19064">variable_name</span></p></th>
+<th rowspan="3" class="cl-35e420d6"><p class="cl-35e40240"><span class="cl-35e19064">variable_level</span></p></th>
+<th rowspan="3" class="cl-35e420d6"><p class="cl-35e40240"><span class="cl-35e19064">estimate_name</span></p></th>
+<th colspan="4" class="cl-35e420e0"><p class="cl-35e40240"><span class="cl-35e19064">Stratifications</span></p></th>
+</tr>
+<tr style="overflow-wrap:break-word;"><th colspan="4" class="cl-35e420e1"><p class="cl-35e40240"><span class="cl-35e19064">age_group and sex</span></p></th></tr>
+<tr style="overflow-wrap:break-word;">
+<th class="cl-35e420e1"><p class="cl-35e40240"><span class="cl-35e19064">&lt;40 and Male</span></p></th>
+<th class="cl-35e420e1"><p class="cl-35e40240"><span class="cl-35e19064">&gt;=40 and Male</span></p></th>
+<th class="cl-35e420e1"><p class="cl-35e40240"><span class="cl-35e19064">&lt;40 and Female</span></p></th>
+<th class="cl-35e420e1"><p class="cl-35e40240"><span class="cl-35e19064">&gt;=40 and Female</span></p></th>
+</tr>
+</thead>
+<tbody>
+<tr style="overflow-wrap:break-word;">
+<td class="cl-35e420e2"><p class="cl-35e4024a"><span class="cl-35e1906e">cohort2</span></p></td>
+<td colspan="7" class="cl-35e420e2"><p class="cl-35e4024a"><span class="cl-35e1906e"></span></p></td>
+</tr>
+<tr style="overflow-wrap:break-word;">
+<td class="cl-35e420eb"><p class="cl-35e4024a"><span class="cl-35e1906f"></span></p></td>
+<td class="cl-35e420ec"><p class="cl-35e4024a"><span class="cl-35e1906f">number subjects</span></p></td>
+<td class="cl-35e420ec"><p class="cl-35e4024a"><span class="cl-35e1906f">-</span></p></td>
+<td class="cl-35e420ec"><p class="cl-35e4024a"><span class="cl-35e1906f">N</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">7,353,196</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">1,959,567</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">9,805,397</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">7,415,215</span></p></td>
+</tr>
+<tr style="overflow-wrap:break-word;">
+<td class="cl-35e420eb"><p class="cl-35e4024a"><span class="cl-35e1906f"></span></p></td>
+<td class="cl-35e420ec"><p class="cl-35e4024a"><span class="cl-35e1906f">age</span></p></td>
+<td class="cl-35e420ec"><p class="cl-35e4024a"><span class="cl-35e1906f">-</span></p></td>
+<td class="cl-35e420ec"><p class="cl-35e4024a"><span class="cl-35e1906f">Mean (SD)</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">68.0163 (0.6522)</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">49.8846 (3.5421)</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">64.1679 (8.2520)</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">66.0284 (2.7382)</span></p></td>
+</tr>
+<tr style="overflow-wrap:break-word;">
+<td class="cl-35e420eb"><p class="cl-35e4024a"><span class="cl-35e1906f"></span></p></td>
+<td class="cl-35e420ec"><p class="cl-35e4024a"><span class="cl-35e1906f">Medications</span></p></td>
+<td class="cl-35e420ec"><p class="cl-35e4024a"><span class="cl-35e1906f">Amoxiciline</span></p></td>
+<td class="cl-35e420ec"><p class="cl-35e4024a"><span class="cl-35e1906f">N (%)</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">37,697 (71.83%)</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">55,991 (24.13%)</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">85,708 (54.70%)</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">38,481 (83.48%)</span></p></td>
+</tr>
+<tr style="overflow-wrap:break-word;">
+<td class="cl-35e420eb"><p class="cl-35e4024a"><span class="cl-35e1906f"></span></p></td>
+<td class="cl-35e420f5"><p class="cl-35e4024a"><span class="cl-35e1906f"></span></p></td>
+<td class="cl-35e420ec"><p class="cl-35e4024a"><span class="cl-35e1906f">Ibuprofen</span></p></td>
+<td class="cl-35e420ec"><p class="cl-35e4024a"><span class="cl-35e1906f">N (%)</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">1,148 (16.46%)</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">88,825 (66.32%)</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">99,635 (85.66%)</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">50,019 (92.65%)</span></p></td>
+</tr>
+<tr style="overflow-wrap:break-word;">
+<td class="cl-35e420e2"><p class="cl-35e4024a"><span class="cl-35e1906e">cohort1</span></p></td>
+<td colspan="7" class="cl-35e420e2"><p class="cl-35e4024a"><span class="cl-35e1906e"></span></p></td>
+</tr>
+<tr style="overflow-wrap:break-word;">
+<td class="cl-35e420eb"><p class="cl-35e4024a"><span class="cl-35e1906f"></span></p></td>
+<td class="cl-35e420ec"><p class="cl-35e4024a"><span class="cl-35e1906f">number subjects</span></p></td>
+<td class="cl-35e420ec"><p class="cl-35e4024a"><span class="cl-35e1906f">-</span></p></td>
+<td class="cl-35e420ec"><p class="cl-35e4024a"><span class="cl-35e1906f">N</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">3,203,857</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">4,023,282</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">1,956,698</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">4,035,381</span></p></td>
+</tr>
+<tr style="overflow-wrap:break-word;">
+<td class="cl-35e420eb"><p class="cl-35e4024a"><span class="cl-35e1906f"></span></p></td>
+<td class="cl-35e420ec"><p class="cl-35e4024a"><span class="cl-35e1906f">age</span></p></td>
+<td class="cl-35e420ec"><p class="cl-35e4024a"><span class="cl-35e1906f">-</span></p></td>
+<td class="cl-35e420ec"><p class="cl-35e4024a"><span class="cl-35e1906f">Mean (SD)</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">22.5563 (3.8918)</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">30.0831 (4.6119)</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">63.6466 (3.1524)</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">47.9025 (1.7468)</span></p></td>
+</tr>
+<tr style="overflow-wrap:break-word;">
+<td class="cl-35e420eb"><p class="cl-35e4024a"><span class="cl-35e1906f"></span></p></td>
+<td class="cl-35e420ec"><p class="cl-35e4024a"><span class="cl-35e1906f">Medications</span></p></td>
+<td class="cl-35e420ec"><p class="cl-35e4024a"><span class="cl-35e1906f">Amoxiciline</span></p></td>
+<td class="cl-35e420ec"><p class="cl-35e4024a"><span class="cl-35e1906f">N (%)</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">54,248 (92.00%)</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">54,460 (40.07%)</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">27,860 (21.32%)</span></p></td>
+<td class="cl-35e420f4"><p class="cl-35e40254"><span class="cl-35e1906f">44,670 (67.18%)</span></p></td>
+</tr>
+<tr style="overflow-wrap:break-word;">
+<td class="cl-35e420f6"><p class="cl-35e4024a"><span class="cl-35e1906f"></span></p></td>
+<td class="cl-35e420fe"><p class="cl-35e4024a"><span class="cl-35e1906f"></span></p></td>
+<td class="cl-35e420ff"><p class="cl-35e4024a"><span class="cl-35e1906f">Ibuprofen</span></p></td>
+<td class="cl-35e420ff"><p class="cl-35e4024a"><span class="cl-35e1906f">N (%)</span></p></td>
+<td class="cl-35e42100"><p class="cl-35e40254"><span class="cl-35e1906f">21,843 (56.69%)</span></p></td>
+<td class="cl-35e42100"><p class="cl-35e40254"><span class="cl-35e1906f">41,836 (25.30%)</span></p></td>
+<td class="cl-35e42100"><p class="cl-35e40254"><span class="cl-35e1906f">66,887 (91.88%)</span></p></td>
+<td class="cl-35e42100"><p class="cl-35e40254"><span class="cl-35e1906f">50,765 (86.74%)</span></p></td>
+</tr>
+</tbody>
+</table>
+</div>
+</div>
+</div>
+</div>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
+    </nav></aside>
+</div>
+
+
+
+    <footer><div class="pkgdown-footer-left">
+  <p>Developed by Martí Català, Núria Mercadé-Besora.</p>
+</div>
+
+<div class="pkgdown-footer-right">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
+</div>
+
+    </footer>
+</div>
+
+
+
+
+
+  </body>
+</html>
diff --git a/articles/a01_tables_files/tabwid-1.1.3/tabwid.css b/articles/a01_tables_files/tabwid-1.1.3/tabwid.css
new file mode 100644
index 0000000..5e31a86
--- /dev/null
+++ b/articles/a01_tables_files/tabwid-1.1.3/tabwid.css
@@ -0,0 +1,42 @@
+.tabwid {
+  font-size: initial;
+  padding-bottom: 1em;
+}
+
+.tabwid table{
+  border-spacing:0px !important;
+  border-collapse:collapse;
+  line-height:1;
+  margin-left:auto;
+  margin-right:auto;
+  border-width: 0;
+  border-color: transparent;
+  caption-side: top;
+}
+.tabwid-caption-bottom table{
+  caption-side: bottom;
+}
+.tabwid_left table{
+  margin-left:0;
+}
+.tabwid_right table{
+  margin-right:0;
+}
+.tabwid td, .tabwid th {
+    padding: 0;
+}
+.tabwid a {
+  text-decoration: none;
+}
+.tabwid thead {
+    background-color: transparent;
+}
+.tabwid tfoot {
+    background-color: transparent;
+}
+.tabwid table tr {
+background-color: transparent;
+}
+.katex-display {
+    margin: 0 0 !important;
+}
diff --git a/articles/a01_tables_files/tabwid-1.1.3/tabwid.js b/articles/a01_tables_files/tabwid-1.1.3/tabwid.js
new file mode 100644
index 0000000..62d3f73
--- /dev/null
+++ b/articles/a01_tables_files/tabwid-1.1.3/tabwid.js
@@ -0,0 +1,31 @@
+document.addEventListener("DOMContentLoaded", function(event) {
+  var els = document.querySelectorAll(".tabwid");
+  var tabwid_link = document.querySelector('link[href*="tabwid.css"]')
+  if (tabwid_link === null) {
+    const tabwid_styles = document.evaluate("//style[contains(., 'tabwid')]", document, null, XPathResult.ANY_TYPE, null );
+    tabwid_link = tabwid_styles.iterateNext();
+  }
+
+  Array.prototype.forEach.call(els, function(template) {
+      const dest = document.createElement("div");
+      template.parentNode.insertBefore(dest, template.nextSibling)
+      dest.setAttribute("class", "flextable-shadow-host");
+      const fantome = dest.attachShadow({mode: 'open'});
+      fantome.appendChild(template);
+      if (tabwid_link !== null) {
+        fantome.appendChild(tabwid_link.cloneNode(true));
+      }
+  });
+
+  const shadowHosts = document.querySelectorAll('.flextable-shadow-host:not(:has(div > table.no-shadow-dom))');
+  shadowHosts.forEach(host => {
+    if (host.shadowRoot) {
+      const spanElements = host.shadowRoot.querySelector('div > table > caption > span[id]');
+      if (spanElements) {
+        const id = spanElements.getAttribute("id");
+        host.setAttribute("id", id);
+      }
+    }
+  });
+
+});
diff --git a/articles/a02_plots.html b/articles/a02_plots.html
new file mode 100644
index 0000000..3529811
--- /dev/null
+++ b/articles/a02_plots.html
@@ -0,0 +1,401 @@
+<!DOCTYPE html>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en">
+<head>
+<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
+<meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
+<title>Plots • visOmopResults</title>
+<!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
+<link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png">
+<link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png">
+<link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png">
+<link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png">
+<link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png">
+<script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
+<link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet">
+<script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet">
+<link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet">
+<script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Plots">
+</head>
+<body>
+    <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
+
+
+    <nav class="navbar navbar-expand-lg fixed-top bg-light" data-bs-theme="light" aria-label="Site navigation"><div class="container">
+
+    <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
+
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
+
+
+    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
+      <span class="navbar-toggler-icon"></span>
+    </button>
+
+    <div id="navbar" class="collapse navbar-collapse ms-3">
+      <ul class="navbar-nav me-auto">
+<li class="nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
+<li class="active nav-item dropdown">
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles">
+<li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
+  </ul>
+</li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul>
+<ul class="navbar-nav">
+<li class="nav-item"><form class="form-inline" role="search">
+ <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json">
+</form></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+      </ul>
+</div>
+
+
+  </div>
+</nav><div class="container template-article">
+
+
+
+
+<div class="row">
+  <main id="main" class="col-md-9"><div class="page-header">
+      <img src="../logo.png" class="logo" alt=""><h1>Plots</h1>
+            
+      
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/vignettes/a02_plots.Rmd" class="external-link"><code>vignettes/a02_plots.Rmd</code></a></small>
+      <div class="d-none name"><code>a02_plots.Rmd</code></div>
+    </div>
+
+    
+    
+<p><strong>visOmopResults</strong> provides plotting tools that simplify
+visualising data in <code>&lt;summarised_result&gt;</code> format while
+also being compatible with other formats.</p>
+<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://darwin-eu.github.io/visOmopResults/">visOmopResults</a></span><span class="op">)</span></span></code></pre></div>
+<div class="section level2">
+<h2 id="plotting-with-a-summarised_result">Plotting with a <code>&lt;summarised_result&gt;</code><a class="anchor" aria-label="anchor" href="#plotting-with-a-summarised_result"></a>
+</h2>
+<p>For this vignette, we will use the <code>penguins</code> dataset from
+the <strong>palmerpenguins</strong> package. This dataset will be
+summarised using the <code><a href="https://darwin-eu.github.io/PatientProfiles/reference/summariseResult.html" class="external-link">PatientProfiles::summariseResult()</a></code>
+function, which aggregates the data into the
+<code>&lt;summarised_result&gt;</code> format:</p>
+<div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://darwin-eu.github.io/PatientProfiles/" class="external-link">PatientProfiles</a></span><span class="op">)</span></span>
+<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://allisonhorst.github.io/palmerpenguins/" class="external-link">palmerpenguins</a></span><span class="op">)</span></span>
+<span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span>
+<span></span>
+<span><span class="va">summariseIsland</span> <span class="op">&lt;-</span> <span class="kw">function</span><span class="op">(</span><span class="va">island</span><span class="op">)</span> <span class="op">{</span></span>
+<span>  <span class="va">penguins</span> <span class="op">|&gt;</span></span>
+<span>    <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">.data</span><span class="op">$</span><span class="va">island</span> <span class="op">==</span> <span class="va">.env</span><span class="op">$</span><span class="va">island</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>    <span class="fu"><a href="https://darwin-eu.github.io/PatientProfiles/reference/summariseResult.html" class="external-link">summariseResult</a></span><span class="op">(</span></span>
+<span>      group <span class="op">=</span> <span class="st">"species"</span>,</span>
+<span>      includeOverallGroup <span class="op">=</span> <span class="cn">TRUE</span>,</span>
+<span>      strata <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"year"</span>, <span class="st">"sex"</span>, <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"year"</span>, <span class="st">"sex"</span><span class="op">)</span><span class="op">)</span>,</span>
+<span>      variables <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span></span>
+<span>        <span class="st">"bill_length_mm"</span>, <span class="st">"bill_depth_mm"</span>, <span class="st">"flipper_length_mm"</span>, <span class="st">"body_mass_g"</span>, </span>
+<span>        <span class="st">"sex"</span><span class="op">)</span>,</span>
+<span>      estimates <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span></span>
+<span>        <span class="st">"median"</span>, <span class="st">"q25"</span>, <span class="st">"q75"</span>, <span class="st">"min"</span>, <span class="st">"max"</span>, <span class="st">"count_missing"</span>, <span class="st">"count"</span>, </span>
+<span>        <span class="st">"percentage"</span>, <span class="st">"density"</span><span class="op">)</span></span>
+<span>    <span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>    <span class="fu"><a href="https://rdrr.io/r/base/message.html" class="external-link">suppressMessages</a></span><span class="op">(</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>    <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>cdm_name <span class="op">=</span> <span class="va">island</span><span class="op">)</span></span>
+<span><span class="op">}</span></span>
+<span></span>
+<span><span class="va">penguinsSummary</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://darwin-eu.github.io/omopgenerics/reference/bind.html" class="external-link">bind</a></span><span class="op">(</span></span>
+<span>  <span class="fu">summariseIsland</span><span class="op">(</span><span class="st">"Torgersen"</span><span class="op">)</span>, </span>
+<span>  <span class="fu">summariseIsland</span><span class="op">(</span><span class="st">"Biscoe"</span><span class="op">)</span>, </span>
+<span>  <span class="fu">summariseIsland</span><span class="op">(</span><span class="st">"Dream"</span><span class="op">)</span></span>
+<span><span class="op">)</span></span>
+<span></span>
+<span><span class="va">penguinsSummary</span> <span class="op">|&gt;</span> <span class="fu"><a href="https://pillar.r-lib.org/reference/glimpse.html" class="external-link">glimpse</a></span><span class="op">(</span><span class="op">)</span></span>
+<span><span class="co">#&gt; Rows: 429,296</span></span>
+<span><span class="co">#&gt; Columns: 13</span></span>
+<span><span class="co">#&gt; $ result_id        <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…</span></span>
+<span><span class="co">#&gt; $ cdm_name         <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "Torgersen", "Torgersen", "Torgersen", "Torgersen", "…</span></span>
+<span><span class="co">#&gt; $ group_name       <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "overall", "overall", "overall", "overall", "overall"…</span></span>
+<span><span class="co">#&gt; $ group_level      <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "overall", "overall", "overall", "overall", "overall"…</span></span>
+<span><span class="co">#&gt; $ strata_name      <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "overall", "overall", "overall", "overall", "overall"…</span></span>
+<span><span class="co">#&gt; $ strata_level     <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "overall", "overall", "overall", "overall", "overall"…</span></span>
+<span><span class="co">#&gt; $ variable_name    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "number records", "bill_length_mm", "bill_length_mm",…</span></span>
+<span><span class="co">#&gt; $ variable_level   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, "density_001", "density_0…</span></span>
+<span><span class="co">#&gt; $ estimate_name    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "count", "median", "q25", "q75", "min", "max", "count…</span></span>
+<span><span class="co">#&gt; $ estimate_type    <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "integer", "numeric", "numeric", "numeric", "numeric"…</span></span>
+<span><span class="co">#&gt; $ estimate_value   <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "52", "38.9", "36.65", "41.1", "33.5", "46", "1", "29…</span></span>
+<span><span class="co">#&gt; $ additional_name  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "overall", "overall", "overall", "overall", "overall"…</span></span>
+<span><span class="co">#&gt; $ additional_level <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "overall", "overall", "overall", "overall", "overall"…</span></span></code></pre></div>
+<div class="section level3">
+<h3 id="plotting-principles-for-summarised_result-objects">Plotting principles for <code>&lt;summarised_result&gt;</code>
+objects<a class="anchor" aria-label="anchor" href="#plotting-principles-for-summarised_result-objects"></a>
+</h3>
+<p><strong>1) Tidy Format</strong><br>
+When working with <code>&lt;summarised_result&gt;</code> objects, the
+data is internally converted into the tidy format before plotting. This
+is an important distinction because columns such as
+<code>strata_name</code> and <code>strata_level</code> from the original
+<code>&lt;summarised_result&gt;</code> cannot be used directly with the
+plotting functions. Instead, tidy columns should be referenced.</p>
+<p>For more information about the tidy format, refer to the
+<strong>omopgenerics</strong> package vignette on
+<code>&lt;summarised_result&gt;</code> <a href="https://darwin-eu.github.io/omopgenerics/articles/summarised_result.html#tidy-a-summarised_result" class="external-link">here</a>.</p>
+<p>To identify the available tidy columns, use the
+<code><a href="https://darwin-eu.github.io/omopgenerics/reference/tidyColumns.html" class="external-link">tidyColumns()</a></code> function:</p>
+<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="fu"><a href="https://darwin-eu.github.io/omopgenerics/reference/tidyColumns.html" class="external-link">tidyColumns</a></span><span class="op">(</span><span class="va">penguinsSummary</span><span class="op">)</span></span>
+<span><span class="co">#&gt;  [1] "cdm_name"       "species"        "year"           "sex"           </span></span>
+<span><span class="co">#&gt;  [5] "variable_name"  "variable_level" "count"          "median"        </span></span>
+<span><span class="co">#&gt;  [9] "q25"            "q75"            "min"            "max"           </span></span>
+<span><span class="co">#&gt; [13] "count_missing"  "density_x"      "density_y"      "percentage"</span></span></code></pre></div>
+<p><strong>2) Subsetting Variables</strong><br>
+Before calling the plotting functions, always subset the
+<code>&lt;summarised_result&gt;</code> object to the variable of
+interest. Avoid combining results from unrelated variables, as this may
+lead to NA values in the tidy format, which can affect your plots.</p>
+</div>
+<div class="section level3">
+<h3 id="scatter-plot">Scatter plot<a class="anchor" aria-label="anchor" href="#scatter-plot"></a>
+</h3>
+<p>We can create simple scatter plots using the
+<code>plotScatter()</code> let’s see some examples:</p>
+<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="va">penguinsSummary</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">variable_name</span> <span class="op">==</span> <span class="st">"bill_depth_mm"</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://darwin-eu.github.io/omopgenerics/reference/filterStrata.html" class="external-link">filterStrata</a></span><span class="op">(</span><span class="va">year</span> <span class="op">!=</span> <span class="st">"overall"</span>, <span class="va">sex</span> <span class="op">==</span> <span class="st">"overall"</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="../reference/scatterPlot.html">scatterPlot</a></span><span class="op">(</span></span>
+<span>    x <span class="op">=</span> <span class="st">"year"</span>, </span>
+<span>    y <span class="op">=</span> <span class="st">"median"</span>,</span>
+<span>    line <span class="op">=</span> <span class="cn">TRUE</span>, </span>
+<span>    point <span class="op">=</span> <span class="cn">TRUE</span>,</span>
+<span>    ribbon <span class="op">=</span> <span class="cn">FALSE</span>,</span>
+<span>    facet <span class="op">=</span> <span class="st">"cdm_name"</span>,</span>
+<span>    colour <span class="op">=</span> <span class="st">"species"</span></span>
+<span>  <span class="op">)</span></span></code></pre></div>
+<p><img src="a02_plots_files/figure-html/unnamed-chunk-4-1.png" width="691.2"></p>
+<p>Additionally, we can use the function <code><a href="../reference/themeVisOmop.html">themeVisOmop()</a></code> to
+change the default <code>ggplot2</code> style to our default style. Not
+only that, but we can use standard ggplot2 functionalities to the
+returned plot:</p>
+<div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="va">penguinsSummary</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">variable_name</span> <span class="op"><a href="https://rdrr.io/r/base/match.html" class="external-link">%in%</a></span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"bill_length_mm"</span>, <span class="st">"bill_depth_mm"</span><span class="op">)</span><span class="op">)</span><span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://darwin-eu.github.io/omopgenerics/reference/filterStrata.html" class="external-link">filterStrata</a></span><span class="op">(</span><span class="va">year</span> <span class="op">==</span> <span class="st">"overall"</span>, <span class="va">sex</span> <span class="op">==</span> <span class="st">"overall"</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://darwin-eu.github.io/omopgenerics/reference/filterGroup.html" class="external-link">filterGroup</a></span><span class="op">(</span><span class="va">species</span> <span class="op">!=</span> <span class="st">"overall"</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="../reference/scatterPlot.html">scatterPlot</a></span><span class="op">(</span></span>
+<span>    x <span class="op">=</span> <span class="st">"density_x"</span>, </span>
+<span>    y <span class="op">=</span> <span class="st">"density_y"</span>,</span>
+<span>    line <span class="op">=</span> <span class="cn">TRUE</span>, </span>
+<span>    point <span class="op">=</span> <span class="cn">FALSE</span>,</span>
+<span>    ribbon <span class="op">=</span> <span class="cn">FALSE</span>,</span>
+<span>    facet <span class="op">=</span> <span class="va">cdm_name</span> <span class="op">~</span> <span class="va">variable_name</span>,</span>
+<span>    colour <span class="op">=</span> <span class="st">"species"</span></span>
+<span>  <span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="../reference/themeVisOmop.html">themeVisOmop</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/facet_grid.html" class="external-link">facet_grid</a></span><span class="op">(</span><span class="va">cdm_name</span> <span class="op">~</span> <span class="va">variable_name</span>, scales <span class="op">=</span> <span class="st">"free_x"</span><span class="op">)</span> </span></code></pre></div>
+<p><img src="a02_plots_files/figure-html/unnamed-chunk-5-1.png" width="691.2"></p>
+<div class="sourceCode" id="cb6"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="va">penguinsSummary</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">variable_name</span> <span class="op">==</span> <span class="st">"flipper_length_mm"</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://darwin-eu.github.io/omopgenerics/reference/filterStrata.html" class="external-link">filterStrata</a></span><span class="op">(</span><span class="va">year</span> <span class="op">!=</span> <span class="st">"overall"</span>, <span class="va">sex</span> <span class="op"><a href="https://rdrr.io/r/base/match.html" class="external-link">%in%</a></span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"female"</span>, <span class="st">"male"</span><span class="op">)</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="../reference/scatterPlot.html">scatterPlot</a></span><span class="op">(</span></span>
+<span>    x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"year"</span>, <span class="st">"sex"</span><span class="op">)</span>, </span>
+<span>    y <span class="op">=</span> <span class="st">"median"</span>,</span>
+<span>    ymin <span class="op">=</span> <span class="st">"q25"</span>,</span>
+<span>    ymax <span class="op">=</span> <span class="st">"q75"</span>,</span>
+<span>    line <span class="op">=</span> <span class="cn">FALSE</span>, </span>
+<span>    point <span class="op">=</span> <span class="cn">TRUE</span>,</span>
+<span>    ribbon <span class="op">=</span> <span class="cn">FALSE</span>,</span>
+<span>    facet <span class="op">=</span> <span class="va">cdm_name</span> <span class="op">~</span> <span class="va">species</span>,</span>
+<span>    colour <span class="op">=</span> <span class="st">"sex"</span>,</span>
+<span>    group <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"year"</span>, <span class="st">"sex"</span><span class="op">)</span></span>
+<span>  <span class="op">)</span>  <span class="op">+</span></span>
+<span>  <span class="fu"><a href="../reference/themeVisOmop.html">themeVisOmop</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/coord_flip.html" class="external-link">coord_flip</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span>y <span class="op">=</span> <span class="st">"Flipper length (mm)"</span><span class="op">)</span> <span class="op">+</span> </span>
+<span>  <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/theme.html" class="external-link">theme</a></span><span class="op">(</span>axis.text.x <span class="op">=</span> <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/element.html" class="external-link">element_text</a></span><span class="op">(</span>angle <span class="op">=</span> <span class="fl">90</span>, vjust <span class="op">=</span> <span class="fl">0.5</span>, hjust<span class="op">=</span><span class="fl">1</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
+<p><img src="a02_plots_files/figure-html/unnamed-chunk-6-1.png" width="691.2"></p>
+<div class="sourceCode" id="cb7"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="va">penguinsSummary</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span></span>
+<span>    <span class="va">variable_name</span> <span class="op"><a href="https://rdrr.io/r/base/match.html" class="external-link">%in%</a></span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"flipper_length_mm"</span>, <span class="st">"bill_length_mm"</span>, <span class="st">"bill_depth_mm"</span><span class="op">)</span></span>
+<span>  <span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://darwin-eu.github.io/omopgenerics/reference/filterStrata.html" class="external-link">filterStrata</a></span><span class="op">(</span><span class="va">sex</span> <span class="op">==</span> <span class="st">"overall"</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="../reference/scatterPlot.html">scatterPlot</a></span><span class="op">(</span></span>
+<span>    x <span class="op">=</span> <span class="st">"year"</span>, </span>
+<span>    y <span class="op">=</span> <span class="st">"median"</span>,</span>
+<span>    ymin <span class="op">=</span> <span class="st">"min"</span>,</span>
+<span>    ymax <span class="op">=</span> <span class="st">"max"</span>,</span>
+<span>    line <span class="op">=</span> <span class="cn">FALSE</span>, </span>
+<span>    point <span class="op">=</span> <span class="cn">TRUE</span>,</span>
+<span>    ribbon <span class="op">=</span> <span class="cn">TRUE</span>,</span>
+<span>    facet <span class="op">=</span> <span class="va">cdm_name</span> <span class="op">~</span> <span class="va">species</span>,</span>
+<span>    colour <span class="op">=</span> <span class="st">"variable_name"</span>,</span>
+<span>    group <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"variable_name"</span><span class="op">)</span></span>
+<span>  <span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="../reference/themeVisOmop.html">themeVisOmop</a></span><span class="op">(</span>fontsizeRef <span class="op">=</span> <span class="fl">12</span><span class="op">)</span> <span class="op">+</span> </span>
+<span>  <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/theme.html" class="external-link">theme</a></span><span class="op">(</span>axis.text.x <span class="op">=</span> <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/element.html" class="external-link">element_text</a></span><span class="op">(</span>angle <span class="op">=</span> <span class="fl">90</span>, vjust <span class="op">=</span> <span class="fl">0.5</span>, hjust<span class="op">=</span><span class="fl">1</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
+<p><img src="a02_plots_files/figure-html/unnamed-chunk-7-1.png" width="691.2"></p>
+</div>
+<div class="section level3">
+<h3 id="bar-plot">Bar plot<a class="anchor" aria-label="anchor" href="#bar-plot"></a>
+</h3>
+<p>Let’s create a bar plots:</p>
+<div class="sourceCode" id="cb8"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="va">penguinsSummary</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">variable_name</span> <span class="op">==</span> <span class="st">"number records"</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://darwin-eu.github.io/omopgenerics/reference/filterGroup.html" class="external-link">filterGroup</a></span><span class="op">(</span><span class="va">species</span> <span class="op">!=</span> <span class="st">"overall"</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://darwin-eu.github.io/omopgenerics/reference/filterStrata.html" class="external-link">filterStrata</a></span><span class="op">(</span><span class="va">sex</span> <span class="op">!=</span> <span class="st">"overall"</span>, <span class="va">year</span> <span class="op">!=</span> <span class="st">"overall"</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="../reference/barPlot.html">barPlot</a></span><span class="op">(</span></span>
+<span>    x <span class="op">=</span> <span class="st">"year"</span>,</span>
+<span>    y <span class="op">=</span> <span class="st">"count"</span>,</span>
+<span>    colour <span class="op">=</span> <span class="st">"sex"</span>,</span>
+<span>    facet <span class="op">=</span> <span class="va">cdm_name</span> <span class="op">~</span> <span class="va">species</span></span>
+<span>  <span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="../reference/themeVisOmop.html">themeVisOmop</a></span><span class="op">(</span>fontsizeRef <span class="op">=</span> <span class="fl">12</span><span class="op">)</span></span></code></pre></div>
+<p><img src="a02_plots_files/figure-html/unnamed-chunk-8-1.png" width="691.2"></p>
+</div>
+<div class="section level3">
+<h3 id="box-plot">Box plot<a class="anchor" aria-label="anchor" href="#box-plot"></a>
+</h3>
+<p>Let’s create some box plots of their body mass:</p>
+<div class="sourceCode" id="cb9"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="va">penguinsSummary</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">variable_name</span> <span class="op">==</span> <span class="st">"body_mass_g"</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="../reference/boxPlot.html">boxPlot</a></span><span class="op">(</span>x <span class="op">=</span> <span class="st">"year"</span>, facet <span class="op">=</span> <span class="va">species</span> <span class="op">~</span> <span class="va">cdm_name</span>, colour <span class="op">=</span> <span class="st">"sex"</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="../reference/themeVisOmop.html">themeVisOmop</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
+<p><img src="a02_plots_files/figure-html/unnamed-chunk-9-1.png" width="691.2"></p>
+<div class="sourceCode" id="cb10"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="va">penguinsSummary</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">variable_name</span> <span class="op">==</span> <span class="st">"body_mass_g"</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://darwin-eu.github.io/omopgenerics/reference/filterGroup.html" class="external-link">filterGroup</a></span><span class="op">(</span><span class="va">species</span> <span class="op">!=</span> <span class="st">"overall"</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://darwin-eu.github.io/omopgenerics/reference/filterStrata.html" class="external-link">filterStrata</a></span><span class="op">(</span><span class="va">sex</span> <span class="op"><a href="https://rdrr.io/r/base/match.html" class="external-link">%in%</a></span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"female"</span>, <span class="st">"male"</span><span class="op">)</span>, <span class="va">year</span> <span class="op">!=</span> <span class="st">"overall"</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="../reference/boxPlot.html">boxPlot</a></span><span class="op">(</span>x <span class="op">=</span> <span class="st">"cdm_name"</span>, facet <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"sex"</span>, <span class="st">"species"</span><span class="op">)</span>, colour <span class="op">=</span> <span class="st">"year"</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="../reference/themeVisOmop.html">themeVisOmop</a></span><span class="op">(</span>fontsizeRef <span class="op">=</span> <span class="fl">11</span><span class="op">)</span></span></code></pre></div>
+<p><img src="a02_plots_files/figure-html/unnamed-chunk-10-1.png" width="691.2"></p>
+<p>Note that as we didnt specify x there is no levels in the x axis, but
+box plots are produced anyway.</p>
+</div>
+</div>
+<div class="section level2">
+<h2 id="plotting-with-a-data-frame">Plotting with a <code>&lt;data.frame&gt;</code><a class="anchor" aria-label="anchor" href="#plotting-with-a-data-frame"></a>
+</h2>
+<p>Plotting functions can also be used with the usual
+<code>&lt;data.frame&gt;</code>. In this case we will use the tidy
+format of <code>penguinsSummary</code>.</p>
+<div class="sourceCode" id="cb11"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="va">penguinsTidy</span> <span class="op">&lt;-</span> <span class="va">penguinsSummary</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="op">!</span><span class="va">estimate_name</span> <span class="op"><a href="https://rdrr.io/r/base/match.html" class="external-link">%in%</a></span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"density_x"</span>, <span class="st">"density_y"</span><span class="op">)</span><span class="op">)</span> <span class="op">|&gt;</span> <span class="co"># remove density for simplicity</span></span>
+<span>  <span class="fu"><a href="https://generics.r-lib.org/reference/tidy.html" class="external-link">tidy</a></span><span class="op">(</span><span class="op">)</span></span>
+<span><span class="va">penguinsTidy</span> <span class="op">|&gt;</span> <span class="fu"><a href="https://pillar.r-lib.org/reference/glimpse.html" class="external-link">glimpse</a></span><span class="op">(</span><span class="op">)</span></span>
+<span><span class="co">#&gt; Rows: 720</span></span>
+<span><span class="co">#&gt; Columns: 14</span></span>
+<span><span class="co">#&gt; $ cdm_name       <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "Torgersen", "Torgersen", "Torgersen", "Torgersen", "To…</span></span>
+<span><span class="co">#&gt; $ species        <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "overall", "overall", "overall", "overall", "overall", …</span></span>
+<span><span class="co">#&gt; $ year           <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "overall", "overall", "overall", "overall", "overall", …</span></span>
+<span><span class="co">#&gt; $ sex            <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "overall", "overall", "overall", "overall", "overall", …</span></span>
+<span><span class="co">#&gt; $ variable_name  <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> "number records", "bill_length_mm", "bill_depth_mm", "f…</span></span>
+<span><span class="co">#&gt; $ variable_level <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, "female", "male", <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">N</span>…</span></span>
+<span><span class="co">#&gt; $ count          <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> 52, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, 24, 23, 5, 20, 16, 16, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, …</span></span>
+<span><span class="co">#&gt; $ median         <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #BB0000;">NA</span>, 38, 18, 191, 3700, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, 38, 38, …</span></span>
+<span><span class="co">#&gt; $ q25            <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #BB0000;">NA</span>, 36, 17, 187, 3338, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, 37, 35, …</span></span>
+<span><span class="co">#&gt; $ q75            <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #BB0000;">NA</span>, 41, 19, 195, 4000, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, 39, 41, …</span></span>
+<span><span class="co">#&gt; $ min            <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #BB0000;">NA</span>, 33, 15, 176, 2900, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, 34, 33, …</span></span>
+<span><span class="co">#&gt; $ max            <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #BB0000;">NA</span>, 46, 21, 210, 4700, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, 46, 45, …</span></span>
+<span><span class="co">#&gt; $ count_missing  <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #BB0000;">NA</span>, 1, 1, 1, 1, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, 1, 0, 0, 1, 0, …</span></span>
+<span><span class="co">#&gt; $ percentage     <span style="color: #949494; font-style: italic;">&lt;dbl&gt;</span> <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, <span style="color: #BB0000;">NA</span>, 46.153846, 44.230769, 9.615385, <span style="color: #BB0000;">NA</span>,…</span></span></code></pre></div>
+<p>Using this tidy format, we can replicate plots. For instance, we
+recreate the previous example:</p>
+<div class="sourceCode" id="cb12"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="va">penguinsTidy</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span></span>
+<span>    <span class="va">variable_name</span> <span class="op">==</span> <span class="st">"body_mass_g"</span>,</span>
+<span>    <span class="va">species</span> <span class="op">!=</span> <span class="st">"overall"</span>,</span>
+<span>    <span class="va">sex</span> <span class="op"><a href="https://rdrr.io/r/base/match.html" class="external-link">%in%</a></span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"female"</span>, <span class="st">"male"</span><span class="op">)</span>,</span>
+<span>    <span class="va">year</span> <span class="op">!=</span> <span class="st">"overall"</span></span>
+<span>  <span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="../reference/boxPlot.html">boxPlot</a></span><span class="op">(</span>x <span class="op">=</span> <span class="st">"cdm_name"</span>, facet <span class="op">=</span> <span class="va">sex</span> <span class="op">~</span> <span class="va">species</span>, colour <span class="op">=</span> <span class="st">"year"</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="../reference/themeVisOmop.html">themeVisOmop</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
+<p><img src="a02_plots_files/figure-html/unnamed-chunk-12-1.png" width="691.2"></p>
+</div>
+<div class="section level2">
+<h2 id="custom-plotting">Custom plotting<a class="anchor" aria-label="anchor" href="#custom-plotting"></a>
+</h2>
+<p>The tidy format is very useful to apply any other custom ggplot2
+function that we may be interested on:</p>
+<div class="sourceCode" id="cb13"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://ggplot2.tidyverse.org" class="external-link">ggplot2</a></span><span class="op">)</span></span>
+<span><span class="va">penguinsSummary</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">variable_name</span> <span class="op">==</span> <span class="st">"number records"</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://generics.r-lib.org/reference/tidy.html" class="external-link">tidy</a></span><span class="op">(</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggplot.html" class="external-link">ggplot</a></span><span class="op">(</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/aes.html" class="external-link">aes</a></span><span class="op">(</span>x <span class="op">=</span> <span class="va">year</span>, y <span class="op">=</span> <span class="va">sex</span>, fill <span class="op">=</span> <span class="va">count</span>, label <span class="op">=</span> <span class="va">count</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="../reference/themeVisOmop.html">themeVisOmop</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_tile.html" class="external-link">geom_tile</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/scale_viridis.html" class="external-link">scale_fill_viridis_c</a></span><span class="op">(</span>trans <span class="op">=</span> <span class="st">"log"</span><span class="op">)</span> <span class="op">+</span> </span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/geom_text.html" class="external-link">geom_text</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/facet_grid.html" class="external-link">facet_grid</a></span><span class="op">(</span><span class="va">cdm_name</span> <span class="op">~</span> <span class="va">species</span><span class="op">)</span> <span class="op">+</span> </span>
+<span>  <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/theme.html" class="external-link">theme</a></span><span class="op">(</span>axis.text.x <span class="op">=</span> <span class="fu">ggplot2</span><span class="fu">::</span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/element.html" class="external-link">element_text</a></span><span class="op">(</span>angle <span class="op">=</span> <span class="fl">90</span>, vjust <span class="op">=</span> <span class="fl">0.5</span>, hjust<span class="op">=</span><span class="fl">1</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
+<p><img src="a02_plots_files/figure-html/unnamed-chunk-13-1.png" width="691.2"></p>
+</div>
+<div class="section level2">
+<h2 id="combine-with-ggplot2">Combine with <code>ggplot2</code><a class="anchor" aria-label="anchor" href="#combine-with-ggplot2"></a>
+</h2>
+<p>The plotting functions are a wrapper around the ggplot2 package,
+outputs of the plotting functions can be later customised with ggplot2
+and similar tools. For example we can use <code><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">ggplot2::labs()</a></code>
+to change the labels and <code><a href="https://ggplot2.tidyverse.org/reference/theme.html" class="external-link">ggplot2::theme()</a></code> to move the
+location of the legend.</p>
+<div class="sourceCode" id="cb14"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="va">penguinsSummary</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span></span>
+<span>    <span class="va">group_level</span> <span class="op">!=</span> <span class="st">"overall"</span>,</span>
+<span>    <span class="va">strata_name</span> <span class="op">==</span> <span class="st">"year &amp;&amp;&amp; sex"</span>,</span>
+<span>    <span class="op">!</span><span class="fu"><a href="https://rdrr.io/r/base/grep.html" class="external-link">grepl</a></span><span class="op">(</span><span class="st">"NA"</span>, <span class="va">strata_level</span><span class="op">)</span>,</span>
+<span>    <span class="va">variable_name</span> <span class="op">==</span> <span class="st">"body_mass_g"</span><span class="op">)</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="../reference/boxPlot.html">boxPlot</a></span><span class="op">(</span>x <span class="op">=</span> <span class="st">"species"</span>, facet <span class="op">=</span> <span class="va">cdm_name</span> <span class="op">~</span> <span class="va">sex</span>, colour <span class="op">=</span> <span class="st">"year"</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="../reference/themeVisOmop.html">themeVisOmop</a></span><span class="op">(</span>fontsizeRef <span class="op">=</span> <span class="fl">12</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/lims.html" class="external-link">ylim</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">6500</span><span class="op">)</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/labs.html" class="external-link">labs</a></span><span class="op">(</span>x <span class="op">=</span> <span class="st">"My custom x label"</span><span class="op">)</span></span></code></pre></div>
+<p><img src="a02_plots_files/figure-html/unnamed-chunk-14-1.png" width="691.2"></p>
+<p>You can also use <code><a href="https://ggplot2.tidyverse.org/reference/ggsave.html" class="external-link">ggplot2::ggsave()</a></code> to later save one of
+this plots into ‘.png’ file.</p>
+<div class="sourceCode" id="cb15"><pre class="downlit sourceCode r">
+<code class="sourceCode R"><span><span class="fu"><a href="https://ggplot2.tidyverse.org/reference/ggsave.html" class="external-link">ggsave</a></span><span class="op">(</span></span>
+<span>  <span class="st">"figure8.png"</span>, plot <span class="op">=</span> <span class="fu"><a href="https://ggplot2.tidyverse.org/reference/last_plot.html" class="external-link">last_plot</a></span><span class="op">(</span><span class="op">)</span>, device <span class="op">=</span> <span class="st">"png"</span>, width <span class="op">=</span> <span class="fl">15</span>, height <span class="op">=</span> <span class="fl">12</span>, </span>
+<span>  units <span class="op">=</span> <span class="st">"cm"</span>, dpi <span class="op">=</span> <span class="fl">300</span><span class="op">)</span></span></code></pre></div>
+</div>
+<div class="section level2">
+<h2 id="combine-with-plotly">Combine with <code>plotly</code><a class="anchor" aria-label="anchor" href="#combine-with-plotly"></a>
+</h2>
+<p>Although the package currently does not provide any plotly
+functionality ggplots can be easily converted to
+<code>&lt;plotly&gt;</code> ones using the function
+<code><a href="https://rdrr.io/pkg/plotly/man/ggplotly.html" class="external-link">plotly::ggplotly()</a></code>. This can make the interactivity of some
+plots better.</p>
+</div>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
+    </nav></aside>
+</div>
+
+
+
+    <footer><div class="pkgdown-footer-left">
+  <p>Developed by Martí Català, Núria Mercadé-Besora.</p>
+</div>
+
+<div class="pkgdown-footer-right">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
+</div>
+
+    </footer>
+</div>
+
+
+
+
+
+  </body>
+</html>
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diff --git a/articles/index.html b/articles/index.html
index ca9a5be..2ebbc24 100644
--- a/articles/index.html
+++ b/articles/index.html
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -18,9 +18,10 @@
       <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="../articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -38,9 +39,9 @@
       <h3>All vignettes</h3>
       <div class="section-desc"></div>
 
-      <dl><dt><a href="plots.html">Plotting tools</a></dt>
+      <dl><dt><a href="a01_tables.html">Tables</a></dt>
         <dd>
-        </dd><dt><a href="tables.html">Formatting tables</a></dt>
+        </dd><dt><a href="a02_plots.html">Plots</a></dt>
         <dd>
       </dd></dl></div>
   </main></div>
diff --git a/authors.html b/authors.html
index 2a331f8..c7c23c0 100644
--- a/authors.html
+++ b/authors.html
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -18,9 +18,10 @@
       <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -61,17 +62,17 @@ <h2>Authors</h2>
 
     <div class="section level2">
       <h2 id="citation">Citation</h2>
-      <p><small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/v0.5.1/DESCRIPTION" class="external-link"><code>DESCRIPTION</code></a></small></p>
+      <p><small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/DESCRIPTION" class="external-link"><code>DESCRIPTION</code></a></small></p>
 
       <p>Català M, Mercadé-Besora N (2025).
 <em>visOmopResults: Graphs and Tables for OMOP Results</em>.
-R package version 0.5.1, https://github.com/darwin-eu/visOmopResults, <a href="https://darwin-eu.github.io/visOmopResults/">https://darwin-eu.github.io/visOmopResults/</a>.
+R package version 1.0.0, https://github.com/darwin-eu/visOmopResults, <a href="https://darwin-eu.github.io/visOmopResults/">https://darwin-eu.github.io/visOmopResults/</a>.
 </p>
       <pre>@Manual{,
   title = {visOmopResults: Graphs and Tables for OMOP Results},
   author = {Martí Català and Núria Mercadé-Besora},
   year = {2025},
-  note = {R package version 0.5.1, https://github.com/darwin-eu/visOmopResults},
+  note = {R package version 1.0.0, https://github.com/darwin-eu/visOmopResults},
   url = {https://darwin-eu.github.io/visOmopResults/},
 }</pre>
     </div>
diff --git a/index.html b/index.html
index 68f2cdd..0be7303 100644
--- a/index.html
+++ b/index.html
@@ -17,8 +17,8 @@
 <script src="deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet">
 <link href="deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet">
 <script src="deps/headroom-0.11.0/headroom.min.js"></script><script src="deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="deps/search-1.0.0/fuse.min.js"></script><script src="deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="pkgdown.js"></script><meta property="og:title" content="Graphs and Tables for OMOP Results">
-<meta name="description" content="Provides methods to transform omop_result objects into formatted tables and figures, facilitating the visualization of study results working with the Observational Medical Outcomes Partnership (OMOP) Common Data Model.">
-<meta property="og:description" content="Provides methods to transform omop_result objects into formatted tables and figures, facilitating the visualization of study results working with the Observational Medical Outcomes Partnership (OMOP) Common Data Model.">
+<meta name="description" content="Provides methods to transform omop_result objects into formatted tables and figures, facilitating the visualisation of study results working with the Observational Medical Outcomes Partnership (OMOP) Common Data Model.">
+<meta property="og:description" content="Provides methods to transform omop_result objects into formatted tables and figures, facilitating the visualisation of study results working with the Observational Medical Outcomes Partnership (OMOP) Common Data Model.">
 <meta property="og:image" content="https://darwin-eu.github.io/visOmopResults/logo.png">
 </head>
 <body>
@@ -29,7 +29,7 @@
 
     <a class="navbar-brand me-2" href="index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -42,10 +42,11 @@
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
   <ul class="dropdown-menu" aria-labelledby="dropdown-articles">
-<li><a class="dropdown-item" href="articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="articles/tables.html">Formatting tables</a></li>
+<li><a class="dropdown-item" href="articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="articles/a02_plots.html">Plots</a></li>
   </ul>
 </li>
+<li class="nav-item"><a class="nav-link" href="news/index.html">Changelog</a></li>
       </ul>
 <ul class="navbar-nav">
 <li class="nav-item"><form class="form-inline" role="search">
@@ -69,13 +70,13 @@
 <div class="section level2">
 <h2 id="package-overview">Package overview<a class="anchor" aria-label="anchor" href="#package-overview"></a>
 </h2>
-<p><strong>visOmopResults</strong> offers a set of functions tailored to format objects of class <code>&lt;summarised_result&gt;</code> (as defined in <a href="https://cran.r-project.org/package=omopgenerics" class="external-link">omopgenerics</a> package).</p>
-<p>It provides functionality to create formatted <strong>tables</strong> and generate <strong>plots</strong>. These visualizations are highly versatile for reporting results through Shiny apps, RMarkdown, Quarto, and more, supporting various output formats such as HTML, PNG, Word, and PDF.</p>
+<p><strong>visOmopResults</strong> offers a set of functions tailored to format objects of class <code>&lt;summarised_result&gt;</code> (as defined in <a href="https://darwin-eu.github.io/omopgenerics/articles/summarised_result.html" class="external-link">omopgenerics</a> package).</p>
+<p>It provides functionalities to create formatted <strong>tables</strong> and generate <strong>plots</strong>. These visualisations are highly versatile for reporting results through Shiny apps, RMarkdown, Quarto, and more, supporting various output formats such as HTML, PNG, Word, and PDF.</p>
 </div>
 <div class="section level2">
 <h2 id="lets-get-started">Let’s get started<a class="anchor" aria-label="anchor" href="#lets-get-started"></a>
 </h2>
-<p>You can install the latest version of visOmopResults from CRAN:</p>
+<p>You can install the latest version of <strong>visOmopResults</strong> from CRAN:</p>
 <div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html" class="external-link">install.packages</a></span><span class="op">(</span><span class="st">"visOmopResults"</span><span class="op">)</span></span></code></pre></div>
 <p>Or you can install the development version from <a href="https://github.com/darwin-eu/visOmopResults" class="external-link">GitHub</a> with:</p>
@@ -92,7 +93,7 @@ <h2 id="lets-get-started">Let’s get started<a class="anchor" aria-label="ancho
 <li><a href="https://cran.r-project.org/package=CohortSurvival" class="external-link">CohortSurvival</a></li>
 <li><a href="https://cran.r-project.org/package=CohortSymmetry" class="external-link">CohortSymmetry</a></li>
 </ul>
-<p>Although this standard output format is essential, it can sometimes be challenging to manage. The <em>visOmopResults</em> package aims to simplify this process. To demonstrate the package’s functionality, let’s start by using some mock result:</p>
+<p>Although this standard output format is essential, it can sometimes be challenging to manage. The <strong>visOmopResults</strong> package aims to simplify this process. To demonstrate the package’s functionality, let’s start by using some mock results:</p>
 <div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://darwin-eu.github.io/visOmopResults/">visOmopResults</a></span><span class="op">)</span></span>
 <span><span class="va">result</span> <span class="op">&lt;-</span> <span class="fu"><a href="reference/mockSummarisedResult.html">mockSummarisedResult</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
@@ -100,7 +101,7 @@ <h2 id="lets-get-started">Let’s get started<a class="anchor" aria-label="ancho
 <div class="section level2">
 <h2 id="tables-visualisations">Tables visualisations<a class="anchor" aria-label="anchor" href="#tables-visualisations"></a>
 </h2>
-<p>Currently all table functionalities are built around 3 packages: <a href="https://cran.r-project.org/package=tibble" class="external-link">tibble</a>, <a href="https://cran.r-project.org/package=gt" class="external-link">gt</a>, and <a href="https://cran.r-project.org/package=flextable" class="external-link">flextable</a>.</p>
+<p>Currently all table functionalities are built around 4 packages: <a href="https://cran.r-project.org/package=tibble" class="external-link">tibble</a>, <a href="https://cran.r-project.org/package=gt" class="external-link">gt</a>, <a href="https://cran.r-project.org/package=flextable" class="external-link">flextable</a>, and <a href="https://CRAN.R-project.org/package=DT" class="external-link">datatable</a>.</p>
 <p>There are two main functions:</p>
 <ul>
 <li>
@@ -111,15 +112,16 @@ <h2 id="tables-visualisations">Tables visualisations<a class="anchor" aria-label
 <p>Let’s see a simple example:</p>
 <div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="va">result</span> <span class="op">|&gt;</span></span>
+<span>  <span class="fu"><a href="https://darwin-eu.github.io/omopgenerics/reference/filterStrata.html" class="external-link">filterStrata</a></span><span class="op">(</span><span class="va">sex</span> <span class="op">!=</span> <span class="st">"overall"</span> <span class="op">&amp;</span> <span class="va">age_group</span> <span class="op">!=</span> <span class="st">"overall"</span><span class="op">)</span> <span class="op">|&gt;</span></span>
 <span>  <span class="fu"><a href="reference/visOmopTable.html">visOmopTable</a></span><span class="op">(</span></span>
 <span>    type <span class="op">=</span> <span class="st">"flextable"</span>,</span>
 <span>    estimateName <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span></span>
 <span>      <span class="st">"N(%)"</span> <span class="op">=</span> <span class="st">"&lt;count&gt; (&lt;percentage&gt;%)"</span>, </span>
 <span>      <span class="st">"N"</span> <span class="op">=</span> <span class="st">"&lt;count&gt;"</span>, </span>
 <span>      <span class="st">"mean (sd)"</span> <span class="op">=</span> <span class="st">"&lt;mean&gt; (&lt;sd&gt;)"</span><span class="op">)</span>,</span>
-<span>    header <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"sex"</span><span class="op">)</span>,</span>
+<span>    header <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"sex"</span>, <span class="st">"age_group"</span><span class="op">)</span>,</span>
 <span>    settingsColumn <span class="op">=</span> <span class="cn">NULL</span>,</span>
-<span>    groupColumn <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"cohort_name"</span>, <span class="st">"age_group"</span><span class="op">)</span>,</span>
+<span>    groupColumn <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"cohort_name"</span><span class="op">)</span>,</span>
 <span>    rename <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Variable"</span> <span class="op">=</span> <span class="st">"variable_name"</span>, <span class="st">" "</span> <span class="op">=</span> <span class="st">"variable_level"</span><span class="op">)</span>,</span>
 <span>    hide <span class="op">=</span> <span class="st">"cdm_name"</span></span>
 <span>  <span class="op">)</span></span></code></pre></div>
@@ -138,7 +140,8 @@ <h2 id="plots-visualisations">Plots visualisations<a class="anchor" aria-label="
 <li>
 <code>plotBox()</code> to create a box plot.</li>
 </ul>
-<p>Let’s see how we can create a simple boxplot for age using this tool:</p>
+<p>Additionally, the <code><a href="reference/themeVisOmop.html">themeVisOmop()</a></code> function applies a consistent styling to the plots, aligning them with the package’s visual design.</p>
+<p>Let’s see how we can create a simple boxplot for age:</p>
 <div class="sourceCode" id="cb5"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span></span>
 <span><span class="va">result</span> <span class="op">|&gt;</span></span>
@@ -147,7 +150,8 @@ <h2 id="plots-visualisations">Plots visualisations<a class="anchor" aria-label="
 <span>  <span class="fu"><a href="reference/barPlot.html">barPlot</a></span><span class="op">(</span>x <span class="op">=</span> <span class="st">"age_group"</span>, </span>
 <span>          y <span class="op">=</span> <span class="st">"count"</span>,</span>
 <span>          facet <span class="op">=</span> <span class="st">"cohort_name"</span>, </span>
-<span>          colour <span class="op">=</span> <span class="st">"sex"</span><span class="op">)</span></span></code></pre></div>
+<span>          colour <span class="op">=</span> <span class="st">"sex"</span><span class="op">)</span> <span class="op">+</span></span>
+<span>  <span class="fu"><a href="reference/themeVisOmop.html">themeVisOmop</a></span><span class="op">(</span>fontsizeRef <span class="op">=</span> <span class="fl">12</span><span class="op">)</span></span></code></pre></div>
 <p><img src="reference/figures/README-unnamed-chunk-6-1.png" width="100%"></p>
 </div>
 </div>
@@ -190,7 +194,7 @@ <h2 data-toc-skip>Dev status</h2>
 <ul class="list-unstyled">
 <li><a href="https://github.com/darwin-eu/visOmopResults/actions/workflows/R-CMD-check.yaml" class="external-link"><img src="https://github.com/darwin-eu/visOmopResults/actions/workflows/R-CMD-check.yaml/badge.svg" alt="R-CMD-check"></a></li>
 <li><a href="https://CRAN.R-project.org/package=visOmopResults" class="external-link"><img src="https://www.r-pkg.org/badges/version/visOmopResults" alt="CRAN status"></a></li>
-<li><a href="https://lifecycle.r-lib.org/articles/stages.html#experimental" class="external-link"><img src="https://img.shields.io/badge/lifecycle-experimental-orange.svg" alt="Lifecycle:experimental"></a></li>
+<li><a href="https://lifecycle.r-lib.org/articles/stages.html#stable" class="external-link"><img src="https://img.shields.io/badge/lifecycle-stable-brightgreen.svg" alt="Lifecycle:stable"></a></li>
 <li><a href="https://app.codecov.io/gh/darwin-eu/visOmopResults?branch=main" class="external-link"><img src="https://codecov.io/gh/darwin-eu/visOmopResults/branch/main/graph/badge.svg" alt="Codecov test coverage"></a></li>
 </ul>
 </div>
diff --git a/news/index.html b/news/index.html
new file mode 100644
index 0000000..43ff2fb
--- /dev/null
+++ b/news/index.html
@@ -0,0 +1,61 @@
+<!DOCTYPE html>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Changelog • visOmopResults</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Changelog"><meta property="og:image" content="https://darwin-eu.github.io/visOmopResults/logo.png"></head><body>
+    <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
+
+
+    <nav class="navbar navbar-expand-lg fixed-top bg-light" data-bs-theme="light" aria-label="Site navigation"><div class="container">
+
+    <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
+
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
+
+
+    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
+      <span class="navbar-toggler-icon"></span>
+    </button>
+
+    <div id="navbar" class="collapse navbar-collapse ms-3">
+      <ul class="navbar-nav me-auto"><li class="nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
+<li class="nav-item dropdown">
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
+  </ul></li>
+<li class="active nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
+ <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+      </ul></div>
+
+
+  </div>
+</nav><div class="container template-news">
+<div class="row">
+  <main id="main" class="col-md-9"><div class="page-header">
+      <img src="../logo.png" class="logo" alt=""><h1>Changelog</h1>
+      <small>Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/NEWS.md" class="external-link"><code>NEWS.md</code></a></small>
+    </div>
+
+    <div class="section level2">
+<h2 class="pkg-version" data-toc-text="1.0.0" id="visomopresults-100">visOmopResults 1.0.0<a class="anchor" aria-label="anchor" href="#visomopresults-100"></a></h2>
+<ul><li>Added a <code>NEWS.md</code> file to track changes to the package.</li>
+</ul></div>
+  </main></div>
+
+
+    <footer><div class="pkgdown-footer-left">
+  <p>Developed by Martí Català, Núria Mercadé-Besora.</p>
+</div>
+
+<div class="pkgdown-footer-right">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
+</div>
+
+    </footer></div>
+
+
+
+
+
+  </body></html>
+
diff --git a/pkgdown.yml b/pkgdown.yml
index 2a70d0c..afacf10 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -2,9 +2,9 @@ pandoc: 3.1.11
 pkgdown: 2.1.1
 pkgdown_sha: ~
 articles:
-  plots: plots.html
-  tables: tables.html
-last_built: 2025-01-15T10:02Z
+  a01_tables: a01_tables.html
+  a02_plots: a02_plots.html
+last_built: 2025-01-15T22:15Z
 urls:
   reference: https://darwin-eu.github.io/visOmopResults/reference
   article: https://darwin-eu.github.io/visOmopResults/articles
diff --git a/reference/barPlot.html b/reference/barPlot.html
index bd3dcc2..93ada8a 100644
--- a/reference/barPlot.html
+++ b/reference/barPlot.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Create a bar plot visualisation from a &lt;summarised_result&gt; object — barPlot • visOmopResults</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Create a bar plot visualisation from a &lt;summarised_result&gt; object — barPlot"><meta name="description" content=""><meta property="og:description" content=""><meta property="og:image" content="https://darwin-eu.github.io/visOmopResults/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Create a bar plot visualisation from a &lt;summarised_result&gt; object — barPlot • visOmopResults</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Create a bar plot visualisation from a &lt;summarised_result&gt; object — barPlot"><meta name="description" content="Create a bar plot visualisation from a &amp;lt;summarised_result&amp;gt; object"><meta property="og:description" content="Create a bar plot visualisation from a &amp;lt;summarised_result&amp;gt; object"><meta property="og:image" content="https://darwin-eu.github.io/visOmopResults/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -18,9 +18,10 @@
       <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="../articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -32,12 +33,12 @@
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.png" class="logo" alt=""><h1>Create a bar plot visualisation from a <code>&lt;summarised_result&gt;</code> object</h1>
-      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/v0.5.1/R/plot.R" class="external-link"><code>R/plot.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/R/plot.R" class="external-link"><code>R/plot.R</code></a></small>
       <div class="d-none name"><code>barPlot.Rd</code></div>
     </div>
 
     <div class="ref-description section level2">
-    <p><a href="https://lifecycle.r-lib.org/articles/stages.html#experimental" class="external-link"><img src="figures/lifecycle-experimental.svg" alt="[Experimental]"></a></p>
+    <p>Create a bar plot visualisation from a <code>&lt;summarised_result&gt;</code> object</p>
     </div>
 
     <div class="section level2">
diff --git a/reference/boxPlot.html b/reference/boxPlot.html
index 7026511..8138393 100644
--- a/reference/boxPlot.html
+++ b/reference/boxPlot.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Create a box plot visualisation from a &lt;summarised_result&gt; object — boxPlot • visOmopResults</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Create a box plot visualisation from a &lt;summarised_result&gt; object — boxPlot"><meta name="description" content=""><meta property="og:description" content=""><meta property="og:image" content="https://darwin-eu.github.io/visOmopResults/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Create a box plot visualisation from a &lt;summarised_result&gt; object — boxPlot • visOmopResults</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Create a box plot visualisation from a &lt;summarised_result&gt; object — boxPlot"><meta name="description" content="Create a box plot visualisation from a &amp;lt;summarised_result&amp;gt; object"><meta property="og:description" content="Create a box plot visualisation from a &amp;lt;summarised_result&amp;gt; object"><meta property="og:image" content="https://darwin-eu.github.io/visOmopResults/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -18,9 +18,10 @@
       <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="../articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -32,12 +33,12 @@
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.png" class="logo" alt=""><h1>Create a box plot visualisation from a <code>&lt;summarised_result&gt;</code> object</h1>
-      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/v0.5.1/R/plot.R" class="external-link"><code>R/plot.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/R/plot.R" class="external-link"><code>R/plot.R</code></a></small>
       <div class="d-none name"><code>boxPlot.Rd</code></div>
     </div>
 
     <div class="ref-description section level2">
-    <p><a href="https://lifecycle.r-lib.org/articles/stages.html#experimental" class="external-link"><img src="figures/lifecycle-experimental.svg" alt="[Experimental]"></a></p>
+    <p>Create a box plot visualisation from a <code>&lt;summarised_result&gt;</code> object</p>
     </div>
 
     <div class="section level2">
diff --git a/reference/customiseText.html b/reference/customiseText.html
index fbecc2b..0c1aa52 100644
--- a/reference/customiseText.html
+++ b/reference/customiseText.html
@@ -1,8 +1,8 @@
 <!DOCTYPE html>
 <!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Apply styling to text or column names — customiseText • visOmopResults</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Apply styling to text or column names — customiseText"><meta name="description" content="This function styles character vectors or column names in a data frame.
-The styling function can be customized, or you can provide specific
+The styling function can be customised, or you can provide specific
 replacements for certain values."><meta property="og:description" content="This function styles character vectors or column names in a data frame.
-The styling function can be customized, or you can provide specific
+The styling function can be customised, or you can provide specific
 replacements for certain values."><meta property="og:image" content="https://darwin-eu.github.io/visOmopResults/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
@@ -11,7 +11,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -22,9 +22,10 @@
       <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="../articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -36,13 +37,13 @@
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.png" class="logo" alt=""><h1>Apply styling to text or column names</h1>
-      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/v0.5.1/R/customiseText.R" class="external-link"><code>R/customiseText.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/R/customiseText.R" class="external-link"><code>R/customiseText.R</code></a></small>
       <div class="d-none name"><code>customiseText.Rd</code></div>
     </div>
 
     <div class="ref-description section level2">
     <p>This function styles character vectors or column names in a data frame.
-The styling function can be customized, or you can provide specific
+The styling function can be customised, or you can provide specific
 replacements for certain values.</p>
     </div>
 
diff --git a/reference/emptyPlot-1.png b/reference/emptyPlot-1.png
new file mode 100644
index 0000000..39c8782
Binary files /dev/null and b/reference/emptyPlot-1.png differ
diff --git a/reference/emptyPlot.html b/reference/emptyPlot.html
new file mode 100644
index 0000000..f495967
--- /dev/null
+++ b/reference/emptyPlot.html
@@ -0,0 +1,80 @@
+<!DOCTYPE html>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Returns an empty plot — emptyPlot • visOmopResults</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Returns an empty plot — emptyPlot"><meta name="description" content="Returns an empty plot"><meta property="og:description" content="Returns an empty plot"><meta property="og:image" content="https://darwin-eu.github.io/visOmopResults/logo.png"></head><body>
+    <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
+
+
+    <nav class="navbar navbar-expand-lg fixed-top bg-light" data-bs-theme="light" aria-label="Site navigation"><div class="container">
+
+    <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
+
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
+
+
+    <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
+      <span class="navbar-toggler-icon"></span>
+    </button>
+
+    <div id="navbar" class="collapse navbar-collapse ms-3">
+      <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
+<li class="nav-item dropdown">
+  <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
+  </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
+      </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
+ <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
+<li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
+      </ul></div>
+
+
+  </div>
+</nav><div class="container template-reference-topic">
+<div class="row">
+  <main id="main" class="col-md-9"><div class="page-header">
+      <img src="../logo.png" class="logo" alt=""><h1>Returns an empty plot</h1>
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/R/plot.R" class="external-link"><code>R/plot.R</code></a></small>
+      <div class="d-none name"><code>emptyPlot.Rd</code></div>
+    </div>
+
+    <div class="ref-description section level2">
+    <p>Returns an empty plot</p>
+    </div>
+
+    <div class="section level2">
+    <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">emptyPlot</span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
+    </div>
+
+    <div class="section level2">
+    <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
+    <p>An empty ggplot object</p>
+    </div>
+
+    <div class="section level2">
+    <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="fu">emptyPlot</span><span class="op">(</span><span class="op">)</span></span></span>
+<span class="r-plt img"><img src="emptyPlot-1.png" alt="" width="700" height="433"></span>
+<span class="r-in"><span></span></span>
+</code></pre></div>
+    </div>
+  </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
+    </nav></aside></div>
+
+
+    <footer><div class="pkgdown-footer-left">
+  <p>Developed by Martí Català, Núria Mercadé-Besora.</p>
+</div>
+
+<div class="pkgdown-footer-right">
+  <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
+</div>
+
+    </footer></div>
+
+
+
+
+
+  </body></html>
+
diff --git a/reference/emptyTable.html b/reference/emptyTable.html
index acf4a94..8ba045b 100644
--- a/reference/emptyTable.html
+++ b/reference/emptyTable.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Returns an empty table — emptyTable • visOmopResults</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Returns an empty table — emptyTable"><meta name="description" content=""><meta property="og:description" content=""><meta property="og:image" content="https://darwin-eu.github.io/visOmopResults/logo.png"><!-- dependencies from examples --><link href="libs/tabwid-1.1.3/tabwid.css" rel="stylesheet"><script src="libs/tabwid-1.1.3/tabwid.js"></script></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Returns an empty table — emptyTable • visOmopResults</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Returns an empty table — emptyTable"><meta name="description" content="Returns an empty table"><meta property="og:description" content="Returns an empty table"><meta property="og:image" content="https://darwin-eu.github.io/visOmopResults/logo.png"><!-- dependencies from examples --><link href="libs/tabwid-1.1.3/tabwid.css" rel="stylesheet"><script src="libs/tabwid-1.1.3/tabwid.js"></script></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -18,9 +18,10 @@
       <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="../articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -32,12 +33,12 @@
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.png" class="logo" alt=""><h1>Returns an empty table</h1>
-      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/v0.5.1/R/visTable.R" class="external-link"><code>R/visTable.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/R/visTable.R" class="external-link"><code>R/visTable.R</code></a></small>
       <div class="d-none name"><code>emptyTable.Rd</code></div>
     </div>
 
     <div class="ref-description section level2">
-    <p><a href="https://lifecycle.r-lib.org/articles/stages.html#experimental" class="external-link"><img src="figures/lifecycle-experimental.svg" alt="[Experimental]"></a></p>
+    <p>Returns an empty table</p>
     </div>
 
     <div class="section level2">
@@ -62,7 +63,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
     <div class="section level2">
     <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="fu">emptyTable</span><span class="op">(</span>type <span class="op">=</span> <span class="st">"flextable"</span><span class="op">)</span></span></span>
-<style></style><div class="tabwid"><style>.cl-cb9cff24{}.cl-cb95428e{font-family:'DejaVu Sans';font-size:11pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-cb993862{margin:0;text-align:right;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-cb99532e{width:1.5in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}</style><table data-quarto-disable-processing="true" class="table cl-cb9cff24"><thead><tr style="overflow-wrap:break-word;"><th class="cl-cb99532e"><p class="cl-cb993862"><span class="cl-cb95428e">Table has no data</span></p></th></tr></thead></table></div><span class="r-in"><span></span></span>
+<style></style><div class="tabwid"><style>.cl-2e0f9638{}.cl-2e09375c{font-family:'DejaVu Sans';font-size:11pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-2e0c7fca{margin:0;text-align:right;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-2e0c9960{width:1.5in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}</style><table data-quarto-disable-processing="true" class="table cl-2e0f9638"><thead><tr style="overflow-wrap:break-word;"><th class="cl-2e0c9960"><p class="cl-2e0c7fca"><span class="cl-2e09375c">Table has no data</span></p></th></tr></thead></table></div><span class="r-in"><span></span></span>
 </code></pre></div>
     </div>
   </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
diff --git a/reference/figures/README-unnamed-chunk-5-1.png b/reference/figures/README-unnamed-chunk-5-1.png
index 578ce0c..18647a6 100644
Binary files a/reference/figures/README-unnamed-chunk-5-1.png and b/reference/figures/README-unnamed-chunk-5-1.png differ
diff --git a/reference/figures/README-unnamed-chunk-6-1.png b/reference/figures/README-unnamed-chunk-6-1.png
index 570ea34..b6e208b 100644
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diff --git a/reference/formatEstimateName.html b/reference/formatEstimateName.html
index c5d07d3..4d2d105 100644
--- a/reference/formatEstimateName.html
+++ b/reference/formatEstimateName.html
@@ -9,7 +9,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -20,9 +20,10 @@
       <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="../articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -34,7 +35,7 @@
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.png" class="logo" alt=""><h1>Formats estimate_name and estimate_value column</h1>
-      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/v0.5.1/R/formatEstimateName.R" class="external-link"><code>R/formatEstimateName.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/R/formatEstimateName.R" class="external-link"><code>R/formatEstimateName.R</code></a></small>
       <div class="d-none name"><code>formatEstimateName.Rd</code></div>
     </div>
 
diff --git a/reference/formatEstimateValue.html b/reference/formatEstimateValue.html
index 58ce216..8cff902 100644
--- a/reference/formatEstimateValue.html
+++ b/reference/formatEstimateValue.html
@@ -9,7 +9,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -20,9 +20,10 @@
       <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="../articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -34,7 +35,7 @@
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.png" class="logo" alt=""><h1>Formats the estimate_value column</h1>
-      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/v0.5.1/R/formatEstimateValue.R" class="external-link"><code>R/formatEstimateValue.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/R/formatEstimateValue.R" class="external-link"><code>R/formatEstimateValue.R</code></a></small>
       <div class="d-none name"><code>formatEstimateValue.Rd</code></div>
     </div>
 
diff --git a/reference/formatHeader.html b/reference/formatHeader.html
index 460f51e..783ebe5 100644
--- a/reference/formatHeader.html
+++ b/reference/formatHeader.html
@@ -11,7 +11,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -22,9 +22,10 @@
       <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="../articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -36,7 +37,7 @@
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.png" class="logo" alt=""><h1>Create a header for gt and flextable objects</h1>
-      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/v0.5.1/R/formatHeader.R" class="external-link"><code>R/formatHeader.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/R/formatHeader.R" class="external-link"><code>R/formatHeader.R</code></a></small>
       <div class="d-none name"><code>formatHeader.Rd</code></div>
     </div>
 
diff --git a/reference/formatTable.html b/reference/formatTable.html
index 5ebd989..50e6988 100644
--- a/reference/formatTable.html
+++ b/reference/formatTable.html
@@ -9,7 +9,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -20,9 +20,10 @@
       <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="../articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -34,7 +35,7 @@
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.png" class="logo" alt=""><h1>Creates a flextable or gt object from a dataframe</h1>
-      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/v0.5.1/R/formatTable.R" class="external-link"><code>R/formatTable.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/R/formatTable.R" class="external-link"><code>R/formatTable.R</code></a></small>
       <div class="d-none name"><code>formatTable.Rd</code></div>
     </div>
 
@@ -156,7 +157,7 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-in"><span>    groupOrder <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"cohort1"</span>, <span class="st">"cohort2"</span><span class="op">)</span>,</span></span>
 <span class="r-in"><span>    merge <span class="op">=</span> <span class="st">"all_columns"</span></span></span>
 <span class="r-in"><span>  <span class="op">)</span></span></span>
-<style></style><div class="tabwid"><style>.cl-cce2bd42{}.cl-ccd90cb6{font-family:'Arial';font-size:15pt;font-weight:bold;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-ccd90cca{font-family:'Arial';font-size:10pt;font-weight:bold;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-ccd90ccb{font-family:'DejaVu Sans';font-size:11pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-ccdc5dc6{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-ccdc5dd0{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 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1.00);border-top: 1.2pt solid rgba(190, 190, 190, 1.00);border-left: 1.2pt solid rgba(190, 190, 190, 1.00);border-right: 1.2pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-ccdc8383{width:0.75in;background-color:rgba(225, 225, 225, 1.00);vertical-align: middle;border-bottom: 1.2pt solid rgba(190, 190, 190, 1.00);border-top: 1.2pt solid rgba(190, 190, 190, 1.00);border-left: 1.2pt solid rgba(190, 190, 190, 1.00);border-right: 1.2pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-ccdc8384{width:0.75in;background-color:rgba(233, 233, 233, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(190, 190, 190, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 1pt solid rgba(190, 190, 190, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-ccdc838c{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-ccdc8396{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-ccdc8397{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-ccdc8398{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1pt solid rgba(190, 190, 190, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-ccdc83a0{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1pt solid rgba(190, 190, 190, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-ccdc83a1{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1pt solid rgba(190, 190, 190, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}</style><table data-quarto-disable-processing="true" class="table cl-cce2bd42"><thead><tr style="overflow-wrap:break-word;"><th colspan="19" class="cl-ccdc8378"><p class="cl-ccdc5dc6"><span class="cl-ccd90cb6">fxTable example</span></p></th></tr><tr style="overflow-wrap:break-word;"><th rowspan="3" class="cl-ccdc8378"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">group_level</span></p></th><th rowspan="3" class="cl-ccdc8378"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">result_id</span></p></th><th rowspan="3" class="cl-ccdc8378"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">cdm_name</span></p></th><th rowspan="3" class="cl-ccdc8378"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">group_name</span></p></th><th rowspan="3" class="cl-ccdc8378"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">variable_name</span></p></th><th rowspan="3" class="cl-ccdc8378"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">variable_level</span></p></th><th rowspan="3" class="cl-ccdc8378"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">estimate_name</span></p></th><th rowspan="3" class="cl-ccdc8378"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">estimate_type</span></p></th><th rowspan="3" class="cl-ccdc8378"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">additional_name</span></p></th><th rowspan="3" class="cl-ccdc8378"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">additional_level</span></p></th><th colspan="9" class="cl-ccdc8382"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">Study strata</span></p></th></tr><tr style="overflow-wrap:break-word;"><th class="cl-ccdc8383"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">overall</span></p></th><th colspan="4" class="cl-ccdc8383"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">age_group &amp;&amp;&amp; sex</span></p></th><th colspan="2" class="cl-ccdc8383"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">sex</span></p></th><th colspan="2" class="cl-ccdc8383"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">age_group</span></p></th></tr><tr style="overflow-wrap:break-word;"><th class="cl-ccdc8383"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">overall</span></p></th><th class="cl-ccdc8383"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">&lt;40 &amp;&amp;&amp; Male</span></p></th><th class="cl-ccdc8383"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">&gt;=40 &amp;&amp;&amp; Male</span></p></th><th class="cl-ccdc8383"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">&lt;40 &amp;&amp;&amp; Female</span></p></th><th class="cl-ccdc8383"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">&gt;=40 &amp;&amp;&amp; Female</span></p></th><th class="cl-ccdc8383"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">Male</span></p></th><th class="cl-ccdc8383"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">Female</span></p></th><th class="cl-ccdc8383"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">&lt;40</span></p></th><th class="cl-ccdc8383"><p class="cl-ccdc5dc6"><span class="cl-ccd90cca">&gt;=40</span></p></th></tr></thead><tbody><tr style="overflow-wrap:break-word;"><td rowspan="7" class="cl-ccdc8384"><p class="cl-ccdc5dd0"><span class="cl-ccd90cca">cohort1</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">1</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">mock</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">cohort_name</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">number subjects</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">--</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">count</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">integer</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">1,333,485</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">9,272,818</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">8,941,227</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">2,036,644</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">2,569,829</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">6,140,056</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">4,414,992</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">3,155,947</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">1,013,138</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">age</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">--</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">mean</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">numeric</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">26.2</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">41.6</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">43.9</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">18.2</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">7.8</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">1.8</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">72.8</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">97.1</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">53.5</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">sd</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">numeric</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">9.6</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">4.5</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">9.8</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">5.4</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">3.6</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">5.0</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">0.7</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">9.7</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">6.5</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">Medications</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">Amoxiciline</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">count</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">integer</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">45,675</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">17,903</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">96,621</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">71,341</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">2,489</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">62,646</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">82,792</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">64,307</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">70,848</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">percentage</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">percentage</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">0.865807477384806</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">43.0898792576045</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">72.493509715423</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">41.2256387062371</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">55.0862395204604</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">15.6360570108518</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">4.30012932047248</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">68.464411306195</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">51.4402497094125</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">Ibuprofen</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">count</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">integer</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">34,970</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">98,267</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">40,885</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">36,087</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">65,251</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">14,356</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">68,080</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">85,929</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">83,863</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">percentage</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">percentage</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">11.3047500839457</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">97.0262279734015</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">64.8082781815901</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">5.6073043262586</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">47.3137095803395</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">29.4625013135374</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">61.0299621941522</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">12.1108880266547</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">62.9416507901624</span></p></td></tr><tr style="overflow-wrap:break-word;"><td rowspan="7" class="cl-ccdc8384"><p class="cl-ccdc5dd0"><span class="cl-ccd90cca">cohort2</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">1</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">mock</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">cohort_name</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">number subjects</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">--</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">count</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">integer</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">2,726,462</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">6,536,994</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">9,278,701</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">266,247</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">5,594,912</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">8,541,737</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">758,830</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">2,058,289</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">4,958,896</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">age</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">--</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">mean</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">numeric</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">16.6</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">5.8</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">45.9</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">62.3</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">59.5</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">74.3</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">52.4</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">49.7</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">1.5</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">sd</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">numeric</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">9.8</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">5.4</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">7.6</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">5.6</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">7.8</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">6.4</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">3.8</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">3.6</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">8.4</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">Medications</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">Amoxiciline</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">count</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">integer</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">87,073</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">28,181</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">17,322</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">10,967</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">58,622</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">85,072</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">92,153</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">67,566</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">35,059</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">percentage</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">percentage</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">94.568784837611</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">84.309694217518</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">6.48830933496356</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">76.2110914569348</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">7.83842522650957</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">13.3507662685588</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">80.9696201002225</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">55.9383239364251</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">73.3729686122388</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8397"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">Ibuprofen</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">count</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">integer</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc838c"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">88,131</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">23,770</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">57,863</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">89,790</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">34,443</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">76,086</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">73,110</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">85,243</span></p></td><td class="cl-ccdc8396"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">97,582</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-ccdc8398"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8398"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8398"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8398"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc8398"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb"></span></p></td><td class="cl-ccdc83a0"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">percentage</span></p></td><td class="cl-ccdc83a0"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">percentage</span></p></td><td class="cl-ccdc83a0"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc83a0"><p class="cl-ccdc5dd0"><span class="cl-ccd90ccb">overall</span></p></td><td class="cl-ccdc83a1"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">71.1955302860588</span></p></td><td class="cl-ccdc83a1"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">61.2082786625251</span></p></td><td class="cl-ccdc83a1"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">3.44292330555618</span></p></td><td class="cl-ccdc83a1"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">66.5890787029639</span></p></td><td class="cl-ccdc83a1"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">65.2967276517302</span></p></td><td class="cl-ccdc83a1"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">45.1858439715579</span></p></td><td class="cl-ccdc83a1"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">51.6804101876915</span></p></td><td class="cl-ccdc83a1"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">67.6610797178</span></p></td><td class="cl-ccdc83a1"><p class="cl-ccdc5dda"><span class="cl-ccd90ccb">88.0933094071224</span></p></td></tr></tbody></table></div><span class="r-in"><span></span></span>
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0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-2f1cede6{margin:0;text-align:right;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-2f1d1014{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.2pt solid rgba(190, 190, 190, 1.00);border-top: 1.2pt solid rgba(190, 190, 190, 1.00);border-left: 1.2pt solid rgba(190, 190, 190, 1.00);border-right: 1.2pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-2f1d101e{width:0.75in;background-color:rgba(200, 200, 200, 1.00);vertical-align: middle;border-bottom: 1.2pt solid rgba(190, 190, 190, 1.00);border-top: 1.2pt solid rgba(190, 190, 190, 1.00);border-left: 1.2pt solid rgba(190, 190, 190, 1.00);border-right: 1.2pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-2f1d101f{width:0.75in;background-color:rgba(225, 225, 225, 1.00);vertical-align: middle;border-bottom: 1.2pt solid rgba(190, 190, 190, 1.00);border-top: 1.2pt solid rgba(190, 190, 190, 1.00);border-left: 1.2pt solid rgba(190, 190, 190, 1.00);border-right: 1.2pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-2f1d1020{width:0.75in;background-color:rgba(233, 233, 233, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(190, 190, 190, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 1pt solid rgba(190, 190, 190, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-2f1d1028{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-2f1d1029{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-2f1d102a{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-2f1d1032{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1pt solid rgba(190, 190, 190, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-2f1d1033{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1pt solid rgba(190, 190, 190, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-2f1d1034{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1pt solid rgba(190, 190, 190, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}</style><table data-quarto-disable-processing="true" class="table cl-2f21f728"><thead><tr style="overflow-wrap:break-word;"><th colspan="19" class="cl-2f1d1014"><p class="cl-2f1cedd2"><span class="cl-2f1a0efa">fxTable example</span></p></th></tr><tr style="overflow-wrap:break-word;"><th rowspan="3" class="cl-2f1d1014"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">group_level</span></p></th><th rowspan="3" class="cl-2f1d1014"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">result_id</span></p></th><th rowspan="3" class="cl-2f1d1014"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">cdm_name</span></p></th><th rowspan="3" class="cl-2f1d1014"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">group_name</span></p></th><th rowspan="3" class="cl-2f1d1014"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">variable_name</span></p></th><th rowspan="3" class="cl-2f1d1014"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">variable_level</span></p></th><th rowspan="3" class="cl-2f1d1014"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">estimate_name</span></p></th><th rowspan="3" class="cl-2f1d1014"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">estimate_type</span></p></th><th rowspan="3" class="cl-2f1d1014"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">additional_name</span></p></th><th rowspan="3" class="cl-2f1d1014"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">additional_level</span></p></th><th colspan="9" class="cl-2f1d101e"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">Study strata</span></p></th></tr><tr style="overflow-wrap:break-word;"><th class="cl-2f1d101f"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">overall</span></p></th><th colspan="4" class="cl-2f1d101f"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">age_group &amp;&amp;&amp; sex</span></p></th><th colspan="2" class="cl-2f1d101f"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">sex</span></p></th><th colspan="2" class="cl-2f1d101f"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">age_group</span></p></th></tr><tr style="overflow-wrap:break-word;"><th class="cl-2f1d101f"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">overall</span></p></th><th class="cl-2f1d101f"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">&lt;40 &amp;&amp;&amp; Male</span></p></th><th class="cl-2f1d101f"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">&gt;=40 &amp;&amp;&amp; Male</span></p></th><th class="cl-2f1d101f"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">&lt;40 &amp;&amp;&amp; Female</span></p></th><th class="cl-2f1d101f"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">&gt;=40 &amp;&amp;&amp; Female</span></p></th><th class="cl-2f1d101f"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">Male</span></p></th><th class="cl-2f1d101f"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">Female</span></p></th><th class="cl-2f1d101f"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">&lt;40</span></p></th><th class="cl-2f1d101f"><p class="cl-2f1cedd2"><span class="cl-2f1a0f04">&gt;=40</span></p></th></tr></thead><tbody><tr style="overflow-wrap:break-word;"><td rowspan="7" class="cl-2f1d1020"><p class="cl-2f1ceddc"><span class="cl-2f1a0f04">cohort1</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">1</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">mock</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">cohort_name</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">number subjects</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">--</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">count</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">integer</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">1,333,485</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">9,272,818</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">8,941,227</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">2,036,644</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">2,569,829</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">6,140,056</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">4,414,992</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">3,155,947</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">1,013,138</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">age</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">--</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">mean</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">numeric</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">26.2</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">41.6</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">43.9</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">18.2</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">7.8</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">1.8</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">72.8</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">97.1</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">53.5</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">sd</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">numeric</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">9.6</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">4.5</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">9.8</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">5.4</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">3.6</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">5.0</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">0.7</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">9.7</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">6.5</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">Medications</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">Amoxiciline</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">count</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">integer</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">45,675</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">17,903</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">96,621</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">71,341</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">2,489</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">62,646</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">82,792</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">64,307</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">70,848</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">percentage</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">percentage</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">0.865807477384806</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">43.0898792576045</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">72.493509715423</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">41.2256387062371</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">55.0862395204604</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">15.6360570108518</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">4.30012932047248</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">68.464411306195</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">51.4402497094125</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">Ibuprofen</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">count</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">integer</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">34,970</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">98,267</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">40,885</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">36,087</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">65,251</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">14,356</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">68,080</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">85,929</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">83,863</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">percentage</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">percentage</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">11.3047500839457</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">97.0262279734015</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">64.8082781815901</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">5.6073043262586</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">47.3137095803395</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">29.4625013135374</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">61.0299621941522</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">12.1108880266547</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">62.9416507901624</span></p></td></tr><tr style="overflow-wrap:break-word;"><td rowspan="7" class="cl-2f1d1020"><p class="cl-2f1ceddc"><span class="cl-2f1a0f04">cohort2</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">1</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">mock</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">cohort_name</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">number subjects</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">--</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">count</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">integer</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">2,726,462</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">6,536,994</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">9,278,701</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">266,247</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">5,594,912</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">8,541,737</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">758,830</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">2,058,289</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">4,958,896</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">age</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">--</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">mean</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">numeric</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">16.6</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">5.8</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">45.9</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">62.3</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">59.5</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">74.3</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">52.4</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">49.7</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">1.5</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">sd</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">numeric</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">9.8</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">5.4</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">7.6</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">5.6</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">7.8</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">6.4</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">3.8</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">3.6</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">8.4</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">Medications</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">Amoxiciline</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">count</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">integer</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">87,073</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">28,181</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">17,322</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">10,967</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">58,622</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">85,072</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">92,153</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">67,566</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">35,059</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">percentage</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">percentage</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">94.568784837611</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">84.309694217518</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">6.48830933496356</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">76.2110914569348</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">7.83842522650957</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">13.3507662685588</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">80.9696201002225</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">55.9383239364251</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">73.3729686122388</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d102a"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">Ibuprofen</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">count</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">integer</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1028"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">88,131</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">23,770</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">57,863</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">89,790</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">34,443</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">76,086</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">73,110</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">85,243</span></p></td><td class="cl-2f1d1029"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">97,582</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-2f1d1032"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d1032"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d1032"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d1032"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d1032"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e"></span></p></td><td class="cl-2f1d1033"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">percentage</span></p></td><td class="cl-2f1d1033"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">percentage</span></p></td><td class="cl-2f1d1033"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1033"><p class="cl-2f1ceddc"><span class="cl-2f1a0f0e">overall</span></p></td><td class="cl-2f1d1034"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">71.1955302860588</span></p></td><td class="cl-2f1d1034"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">61.2082786625251</span></p></td><td class="cl-2f1d1034"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">3.44292330555618</span></p></td><td class="cl-2f1d1034"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">66.5890787029639</span></p></td><td class="cl-2f1d1034"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">65.2967276517302</span></p></td><td class="cl-2f1d1034"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">45.1858439715579</span></p></td><td class="cl-2f1d1034"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">51.6804101876915</span></p></td><td class="cl-2f1d1034"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">67.6610797178</span></p></td><td class="cl-2f1d1034"><p class="cl-2f1cede6"><span class="cl-2f1a0f0e">88.0933094071224</span></p></td></tr></tbody></table></div><span class="r-in"><span></span></span>
 <span class="r-in"><span><span class="co"># Example 2</span></span></span>
 <span class="r-in"><span><span class="fu"><a href="mockSummarisedResult.html">mockSummarisedResult</a></span><span class="op">(</span><span class="op">)</span> <span class="op">|&gt;</span></span></span>
 <span class="r-in"><span>  <span class="fu"><a href="formatEstimateValue.html">formatEstimateValue</a></span><span class="op">(</span>decimals <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>integer <span class="op">=</span> <span class="fl">0</span>, numeric <span class="op">=</span> <span class="fl">1</span><span class="op">)</span><span class="op">)</span> <span class="op">|&gt;</span></span></span>
diff --git a/reference/index.html b/reference/index.html
index cd50655..2cec46f 100644
--- a/reference/index.html
+++ b/reference/index.html
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -18,9 +18,10 @@
       <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="../articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -60,7 +61,7 @@ <h3 id="main-functions">Main functions<a class="anchor" aria-label="anchor" href
       </dl><dl><dt>
 
           <code><a href="visTable.html">visTable()</a></code>
-          <span class="badge lifecycle lifecycle-experimental">experimental</span>
+
         </dt>
         <dd>Generate a formatted table from a <code>&lt;data.table&gt;</code></dd>
       </dl></div><div class="section level2">
@@ -112,7 +113,7 @@ <h3 id="helper-table-functions">Helper table functions<a class="anchor" aria-lab
       <dl><dt>
 
           <code><a href="emptyTable.html">emptyTable()</a></code>
-          <span class="badge lifecycle lifecycle-experimental">experimental</span>
+
         </dt>
         <dd>Returns an empty table</dd>
       </dl><dl><dt>
@@ -153,19 +154,25 @@ <h2 id="plot-functions">Plot functions<a class="anchor" aria-label="anchor" href
       <dl><dt>
 
           <code><a href="barPlot.html">barPlot()</a></code>
-          <span class="badge lifecycle lifecycle-experimental">experimental</span>
+
         </dt>
         <dd>Create a bar plot visualisation from a <code>&lt;summarised_result&gt;</code> object</dd>
       </dl><dl><dt>
 
           <code><a href="boxPlot.html">boxPlot()</a></code>
-          <span class="badge lifecycle lifecycle-experimental">experimental</span>
+
         </dt>
         <dd>Create a box plot visualisation from a <code>&lt;summarised_result&gt;</code> object</dd>
       </dl><dl><dt>
 
+          <code><a href="emptyPlot.html">emptyPlot()</a></code>
+
+        </dt>
+        <dd>Returns an empty plot</dd>
+      </dl><dl><dt>
+
           <code><a href="scatterPlot.html">scatterPlot()</a></code>
-          <span class="badge lifecycle lifecycle-experimental">experimental</span>
+
         </dt>
         <dd>Create a scatter plot visualisation from a <code>&lt;summarised_result&gt;</code> object</dd>
       </dl></div><div class="section level2">
diff --git a/reference/mockSummarisedResult.html b/reference/mockSummarisedResult.html
index 7ca4930..b5adf6c 100644
--- a/reference/mockSummarisedResult.html
+++ b/reference/mockSummarisedResult.html
@@ -9,7 +9,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -20,9 +20,10 @@
       <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="../articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -34,7 +35,7 @@
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.png" class="logo" alt=""><h1>A <code>&lt;summarised_result&gt;</code> object filled with mock data</h1>
-      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/v0.5.1/R/mockResults.R" class="external-link"><code>R/mockResults.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/R/mockResults.R" class="external-link"><code>R/mockResults.R</code></a></small>
       <div class="d-none name"><code>mockSummarisedResult.Rd</code></div>
     </div>
 
diff --git a/reference/plotColumns.html b/reference/plotColumns.html
index 72e92f9..2248327 100644
--- a/reference/plotColumns.html
+++ b/reference/plotColumns.html
@@ -9,7 +9,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -20,9 +20,10 @@
       <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="../articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -34,7 +35,7 @@
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.png" class="logo" alt=""><h1>Columns for the plot functions</h1>
-      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/v0.5.1/R/helperFunctions.R" class="external-link"><code>R/helperFunctions.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/R/helperFunctions.R" class="external-link"><code>R/helperFunctions.R</code></a></small>
       <div class="d-none name"><code>plotColumns.Rd</code></div>
     </div>
 
diff --git a/reference/reexports.html b/reference/reexports.html
index 34c9bc6..d7468cf 100644
--- a/reference/reexports.html
+++ b/reference/reexports.html
@@ -29,7 +29,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -40,9 +40,10 @@
       <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="../articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -54,7 +55,7 @@
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.png" class="logo" alt=""><h1>Objects exported from other packages</h1>
-      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/v0.5.1/R/reexports.R" class="external-link"><code>R/reexports.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/R/reexports.R" class="external-link"><code>R/reexports.R</code></a></small>
       <div class="d-none name"><code>reexports.Rd</code></div>
     </div>
 
diff --git a/reference/scatterPlot.html b/reference/scatterPlot.html
index cdeed66..fb7c4e5 100644
--- a/reference/scatterPlot.html
+++ b/reference/scatterPlot.html
@@ -1,5 +1,5 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Create a scatter plot visualisation from a &lt;summarised_result&gt; object — scatterPlot • visOmopResults</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Create a scatter plot visualisation from a &lt;summarised_result&gt; object — scatterPlot"><meta name="description" content=""><meta property="og:description" content=""><meta property="og:image" content="https://darwin-eu.github.io/visOmopResults/logo.png"></head><body>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Create a scatter plot visualisation from a &lt;summarised_result&gt; object — scatterPlot • visOmopResults</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Create a scatter plot visualisation from a &lt;summarised_result&gt; object — scatterPlot"><meta name="description" content="Create a scatter plot visualisation from a &amp;lt;summarised_result&amp;gt; object"><meta property="og:description" content="Create a scatter plot visualisation from a &amp;lt;summarised_result&amp;gt; object"><meta property="og:image" content="https://darwin-eu.github.io/visOmopResults/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -18,9 +18,10 @@
       <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="../articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -32,12 +33,12 @@
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.png" class="logo" alt=""><h1>Create a scatter plot visualisation from a <code>&lt;summarised_result&gt;</code> object</h1>
-      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/v0.5.1/R/plot.R" class="external-link"><code>R/plot.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/R/plot.R" class="external-link"><code>R/plot.R</code></a></small>
       <div class="d-none name"><code>scatterPlot.Rd</code></div>
     </div>
 
     <div class="ref-description section level2">
-    <p><a href="https://lifecycle.r-lib.org/articles/stages.html#experimental" class="external-link"><img src="figures/lifecycle-experimental.svg" alt="[Experimental]"></a></p>
+    <p>Create a scatter plot visualisation from a <code>&lt;summarised_result&gt;</code> object</p>
     </div>
 
     <div class="section level2">
diff --git a/reference/tableColumns.html b/reference/tableColumns.html
index e868ef1..33ed581 100644
--- a/reference/tableColumns.html
+++ b/reference/tableColumns.html
@@ -9,7 +9,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -20,9 +20,10 @@
       <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="../articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -34,7 +35,7 @@
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.png" class="logo" alt=""><h1>Columns for the table functions</h1>
-      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/v0.5.1/R/helperFunctions.R" class="external-link"><code>R/helperFunctions.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/R/helperFunctions.R" class="external-link"><code>R/helperFunctions.R</code></a></small>
       <div class="d-none name"><code>tableColumns.Rd</code></div>
     </div>
 
diff --git a/reference/tableOptions.html b/reference/tableOptions.html
index 3f70a64..d5317fc 100644
--- a/reference/tableOptions.html
+++ b/reference/tableOptions.html
@@ -9,7 +9,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -20,9 +20,10 @@
       <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="../articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -34,7 +35,7 @@
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.png" class="logo" alt=""><h1>Additional table formatting options for <code>visOmopTable()</code> and <code>visTable()</code></h1>
-      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/v0.5.1/R/helperFunctions.R" class="external-link"><code>R/helperFunctions.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/R/helperFunctions.R" class="external-link"><code>R/helperFunctions.R</code></a></small>
       <div class="d-none name"><code>tableOptions.Rd</code></div>
     </div>
 
@@ -50,7 +51,7 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-    <p>A named list of default options for table customization.</p>
+    <p>A named list of default options for table customisation.</p>
     </div>
 
     <div class="section level2">
diff --git a/reference/tableStyle.html b/reference/tableStyle.html
index c9308ea..3e144e2 100644
--- a/reference/tableStyle.html
+++ b/reference/tableStyle.html
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -18,9 +18,10 @@
       <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="../articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -32,7 +33,7 @@
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.png" class="logo" alt=""><h1>Supported predefined styles for formatted tables</h1>
-      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/v0.5.1/R/helperFunctions.R" class="external-link"><code>R/helperFunctions.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/R/helperFunctions.R" class="external-link"><code>R/helperFunctions.R</code></a></small>
       <div class="d-none name"><code>tableStyle.Rd</code></div>
     </div>
 
@@ -42,7 +43,7 @@
 
     <div class="section level2">
     <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">tableStyle</span><span class="op">(</span>type <span class="op">=</span> <span class="st">"gt"</span>, styleName <span class="op">=</span> <span class="st">"default"</span><span class="op">)</span></span></code></pre></div>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">tableStyle</span><span class="op">(</span>type <span class="op">=</span> <span class="st">"gt"</span><span class="op">)</span></span></code></pre></div>
     </div>
 
     <div class="section level2">
@@ -53,11 +54,6 @@ <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#argumen
 <dd><p>Character string specifying the formatted table class.
 See <code><a href="tableType.html">tableType()</a></code> for supported classes. Default is "gt".</p></dd>
 
-
-<dt id="arg-stylename">styleName<a class="anchor" aria-label="anchor" href="#arg-stylename"></a></dt>
-<dd><p>A character string specifying the style name. Currently, the
-package supports only one predefined style: "default".</p></dd>
-
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
diff --git a/reference/tableType.html b/reference/tableType.html
index fb24bdb..2b77a32 100644
--- a/reference/tableType.html
+++ b/reference/tableType.html
@@ -11,7 +11,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -22,9 +22,10 @@
       <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="../articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -36,7 +37,7 @@
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.png" class="logo" alt=""><h1>Supported table classes</h1>
-      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/v0.5.1/R/helperFunctions.R" class="external-link"><code>R/helperFunctions.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/R/helperFunctions.R" class="external-link"><code>R/helperFunctions.R</code></a></small>
       <div class="d-none name"><code>tableType.Rd</code></div>
     </div>
 
diff --git a/reference/themeVisOmop-1.png b/reference/themeVisOmop-1.png
index 80ebb7c..7b1b90c 100644
Binary files a/reference/themeVisOmop-1.png and b/reference/themeVisOmop-1.png differ
diff --git a/reference/themeVisOmop.html b/reference/themeVisOmop.html
index 09af744..5e42be2 100644
--- a/reference/themeVisOmop.html
+++ b/reference/themeVisOmop.html
@@ -7,7 +7,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -18,9 +18,10 @@
       <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="../articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -32,7 +33,7 @@
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.png" class="logo" alt=""><h1>Apply visOmopResults default styling to a ggplot</h1>
-      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/v0.5.1/R/plottingThemes.R" class="external-link"><code>R/plottingThemes.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/R/plottingThemes.R" class="external-link"><code>R/plottingThemes.R</code></a></small>
       <div class="d-none name"><code>themeVisOmop.Rd</code></div>
     </div>
 
@@ -42,7 +43,7 @@
 
     <div class="section level2">
     <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">themeVisOmop</span><span class="op">(</span>fontsizeRef <span class="op">=</span> <span class="fl">13</span>, legendPosition <span class="op">=</span> <span class="st">"right"</span><span class="op">)</span></span></code></pre></div>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">themeVisOmop</span><span class="op">(</span>fontsizeRef <span class="op">=</span> <span class="fl">10</span><span class="op">)</span></span></code></pre></div>
     </div>
 
     <div class="section level2">
@@ -53,11 +54,6 @@ <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#argumen
 <dd><p>An integer to use as reference when adjusting label
 fontsize.</p></dd>
 
-
-<dt id="arg-legendposition">legendPosition<a class="anchor" aria-label="anchor" href="#arg-legendposition"></a></dt>
-<dd><p>If there is a legend, where should it go? Options are
-the same as for ggplot. By default it is in the right side.</p></dd>
-
 </dl></div>
 
     <div class="section level2">
diff --git a/reference/visOmopResults-package.html b/reference/visOmopResults-package.html
index 6b93581..508d4f5 100644
--- a/reference/visOmopResults-package.html
+++ b/reference/visOmopResults-package.html
@@ -1,7 +1,7 @@
 <!DOCTYPE html>
 <!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>visOmopResults: Graphs and Tables for OMOP Results — visOmopResults-package • visOmopResults</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="visOmopResults: Graphs and Tables for OMOP Results — visOmopResults-package"><meta name="description" content="
-Provides methods to transform omop_result objects into formatted tables and figures, facilitating the visualization of study results working with the Observational Medical Outcomes Partnership (OMOP) Common Data Model."><meta property="og:description" content="
-Provides methods to transform omop_result objects into formatted tables and figures, facilitating the visualization of study results working with the Observational Medical Outcomes Partnership (OMOP) Common Data Model."><meta property="og:image" content="https://darwin-eu.github.io/visOmopResults/logo.png"></head><body>
+Provides methods to transform omop_result objects into formatted tables and figures, facilitating the visualisation of study results working with the Observational Medical Outcomes Partnership (OMOP) Common Data Model."><meta property="og:description" content="
+Provides methods to transform omop_result objects into formatted tables and figures, facilitating the visualisation of study results working with the Observational Medical Outcomes Partnership (OMOP) Common Data Model."><meta property="og:image" content="https://darwin-eu.github.io/visOmopResults/logo.png"></head><body>
     <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
 
 
@@ -9,7 +9,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -20,9 +20,10 @@
       <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="../articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -34,13 +35,13 @@
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.png" class="logo" alt=""><h1>visOmopResults: Graphs and Tables for OMOP Results</h1>
-      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/v0.5.1/R/visOmopResults-package.R" class="external-link"><code>R/visOmopResults-package.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/R/visOmopResults-package.R" class="external-link"><code>R/visOmopResults-package.R</code></a></small>
       <div class="d-none name"><code>visOmopResults-package.Rd</code></div>
     </div>
 
     <div class="ref-description section level2">
     <p></p>
-<p>Provides methods to transform omop_result objects into formatted tables and figures, facilitating the visualization of study results working with the Observational Medical Outcomes Partnership (OMOP) Common Data Model.</p>
+<p>Provides methods to transform omop_result objects into formatted tables and figures, facilitating the visualisation of study results working with the Observational Medical Outcomes Partnership (OMOP) Common Data Model.</p>
     </div>
 
 
@@ -53,8 +54,8 @@ <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"
     </div>
     <div class="section level2">
     <h2 id="author">Author<a class="anchor" aria-label="anchor" href="#author"></a></h2>
-    <p><strong>Maintainer</strong>: Núria Mercadé-Besora <a href="mailto:nuria.mercadebesora@ndorms.ox.ac.uk">nuria.mercadebesora@ndorms.ox.ac.uk</a> (<a href="https://orcid.org/0009-0006-7948-3747" class="external-link">ORCID</a>)</p>
-<p>Authors:</p><ul><li><p>Martí Català <a href="mailto:marti.catalasabate@ndorms.ox.ac.uk">marti.catalasabate@ndorms.ox.ac.uk</a> (<a href="https://orcid.org/0000-0003-3308-9905" class="external-link">ORCID</a>)</p></li>
+    <p><strong>Maintainer</strong>: N&lt;U+00FA&gt;ria Mercad&lt;U+00E9&gt;-Besora <a href="mailto:nuria.mercadebesora@ndorms.ox.ac.uk">nuria.mercadebesora@ndorms.ox.ac.uk</a> (<a href="https://orcid.org/0009-0006-7948-3747" class="external-link">ORCID</a>)</p>
+<p>Authors:</p><ul><li><p>Mart&lt;U+00ED&gt; Catal&lt;U+00E0&gt; <a href="mailto:marti.catalasabate@ndorms.ox.ac.uk">marti.catalasabate@ndorms.ox.ac.uk</a> (<a href="https://orcid.org/0000-0003-3308-9905" class="external-link">ORCID</a>)</p></li>
 </ul><p>Other contributors:</p><ul><li><p>Yuchen Guo <a href="mailto:yuchen.guo@ndorms.ox.ac.uk">yuchen.guo@ndorms.ox.ac.uk</a> (<a href="https://orcid.org/0000-0002-0847-4855" class="external-link">ORCID</a>) [contributor]</p></li>
 <li><p>Elin Rowlands <a href="mailto:elin.rowlands@ndorms.ox.ac.uk">elin.rowlands@ndorms.ox.ac.uk</a> (<a href="https://orcid.org/0009-0007-6629-4661" class="external-link">ORCID</a>) [contributor]</p></li>
 <li><p>Edward Burn <a href="mailto:edward.burn@ndorms.ox.ac.uk">edward.burn@ndorms.ox.ac.uk</a> (<a href="https://orcid.org/0000-0002-9286-1128" class="external-link">ORCID</a>) [contributor]</p></li>
diff --git a/reference/visOmopTable.html b/reference/visOmopTable.html
index 7c86c30..1ae930d 100644
--- a/reference/visOmopTable.html
+++ b/reference/visOmopTable.html
@@ -11,7 +11,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -22,9 +22,10 @@
       <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="../articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -36,7 +37,7 @@
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.png" class="logo" alt=""><h1>Format a <code>&lt;summarised_result&gt;</code> object into a gt, flextable, or tibble object</h1>
-      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/v0.5.1/R/visOmopTable.R" class="external-link"><code>R/visOmopTable.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/R/visOmopTable.R" class="external-link"><code>R/visOmopTable.R</code></a></small>
       <div class="d-none name"><code>visOmopTable.Rd</code></div>
     </div>
 
@@ -60,8 +61,7 @@ <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage">
 <span>  columnOrder <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/character.html" class="external-link">character</a></span><span class="op">(</span><span class="op">)</span>,</span>
 <span>  factor <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="op">)</span>,</span>
 <span>  showMinCellCount <span class="op">=</span> <span class="cn">TRUE</span>,</span>
-<span>  .options <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="op">)</span>,</span>
-<span>  settingsColumns <span class="op">=</span> <span class="fu">lifecycle</span><span class="fu">::</span><span class="fu"><a href="https://lifecycle.r-lib.org/reference/deprecated.html" class="external-link">deprecated</a></span><span class="op">(</span><span class="op">)</span></span>
+<span>  .options <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="op">)</span></span>
 <span><span class="op">)</span></span></code></pre></div>
     </div>
 
@@ -99,11 +99,11 @@ <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#argumen
 named list such as:
 list("newGroupName" = c("variable_name", "variable_level")).</p>
 <p>*tidy: The tidy format applied to column names replaces "_" with a space and
-converts to sentence case. Use <code>rename</code> to customize specific column names.</p></dd>
+converts to sentence case. Use <code>rename</code> to customise specific column names.</p></dd>
 
 
 <dt id="arg-rename">rename<a class="anchor" aria-label="anchor" href="#arg-rename"></a></dt>
-<dd><p>A named vector to customize column names, e.g.,
+<dd><p>A named vector to customise column names, e.g.,
 c("Database name" = "cdm_name"). The function renames all column names
 not specified here into a tidy* format.</p></dd>
 
@@ -141,10 +141,6 @@ <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#argumen
 <dd><p>A named list with additional formatting options.
 <code><a href="tableOptions.html">visOmopResults::tableOptions()</a></code> shows allowed arguments and their default values.</p></dd>
 
-
-<dt id="arg-settingscolumns">settingsColumns<a class="anchor" aria-label="anchor" href="#arg-settingscolumns"></a></dt>
-<dd><p><a href="https://lifecycle.r-lib.org/articles/stages.html#deprecated" class="external-link"><img src="figures/lifecycle-deprecated.svg" alt="[Deprecated]"></a></p></dd>
-
 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
diff --git a/reference/visTable.html b/reference/visTable.html
index 7f33daa..f462db3 100644
--- a/reference/visTable.html
+++ b/reference/visTable.html
@@ -1,11 +1,9 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Generate a formatted table from a &lt;data.table&gt; — visTable • visOmopResults</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Generate a formatted table from a &lt;data.table&gt; — visTable"><meta name="description" content="
-This function combines the functionalities of formatEstimateValue(),
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Generate a formatted table from a &lt;data.table&gt; — visTable • visOmopResults</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Generate a formatted table from a &lt;data.table&gt; — visTable"><meta name="description" content="This function combines the functionalities of formatEstimateValue(),
 formatEstimateName(), formatHeader(), and formatTable()
 into a single function. While it does not require the input table to be
 a &amp;lt;summarised_result&amp;gt;, it does expect specific fields to apply some
-formatting functionalities."><meta property="og:description" content="
-This function combines the functionalities of formatEstimateValue(),
+formatting functionalities."><meta property="og:description" content="This function combines the functionalities of formatEstimateValue(),
 formatEstimateName(), formatHeader(), and formatTable()
 into a single function. While it does not require the input table to be
 a &amp;lt;summarised_result&amp;gt;, it does expect specific fields to apply some
@@ -17,7 +15,7 @@
 
     <a class="navbar-brand me-2" href="../index.html">visOmopResults</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.5.1</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">1.0.0</small>
 
 
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -28,9 +26,10 @@
       <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li>
 <li class="nav-item dropdown">
   <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button>
-  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/plots.html">Plotting tools</a></li>
-    <li><a class="dropdown-item" href="../articles/tables.html">Formatting tables</a></li>
+  <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/a01_tables.html">Tables</a></li>
+    <li><a class="dropdown-item" href="../articles/a02_plots.html">Plots</a></li>
   </ul></li>
+<li class="nav-item"><a class="nav-link" href="../news/index.html">Changelog</a></li>
       </ul><ul class="navbar-nav"><li class="nav-item"><form class="form-inline" role="search">
  <input class="form-control" type="search" name="search-input" id="search-input" autocomplete="off" aria-label="Search site" placeholder="Search for" data-search-index="../search.json"></form></li>
 <li class="nav-item"><a class="external-link nav-link" href="https://github.com/darwin-eu/visOmopResults/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li>
@@ -42,13 +41,12 @@
 <div class="row">
   <main id="main" class="col-md-9"><div class="page-header">
       <img src="../logo.png" class="logo" alt=""><h1>Generate a formatted table from a <code>&lt;data.table&gt;</code></h1>
-      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/v0.5.1/R/visTable.R" class="external-link"><code>R/visTable.R</code></a></small>
+      <small class="dont-index">Source: <a href="https://github.com/darwin-eu/visOmopResults/blob/main/R/visTable.R" class="external-link"><code>R/visTable.R</code></a></small>
       <div class="d-none name"><code>visTable.Rd</code></div>
     </div>
 
     <div class="ref-description section level2">
-    <p><a href="https://lifecycle.r-lib.org/articles/stages.html#experimental" class="external-link"><img src="figures/lifecycle-experimental.svg" alt="[Experimental]"></a>
-This function combines the functionalities of <code><a href="formatEstimateValue.html">formatEstimateValue()</a></code>,
+    <p>This function combines the functionalities of <code><a href="formatEstimateValue.html">formatEstimateValue()</a></code>,
 <code><a href="formatEstimateName.html">formatEstimateName()</a></code>, <code><a href="formatHeader.html">formatHeader()</a></code>, and <code><a href="formatTable.html">formatTable()</a></code>
 into a single function. While it does not require the input table to be
 a <code>&lt;summarised_result&gt;</code>, it does expect specific fields to apply some
@@ -96,11 +94,11 @@ <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#argumen
 group name, use a named list such as:
 list("newGroupName" = c("variable_name", "variable_level")).</p>
 <p>*tidy: The tidy format applied to column names replaces "_" with a space and
-converts them to sentence case. Use <code>rename</code> to customize specific column names.</p></dd>
+converts them to sentence case. Use <code>rename</code> to customise specific column names.</p></dd>
 
 
 <dt id="arg-rename">rename<a class="anchor" aria-label="anchor" href="#arg-rename"></a></dt>
-<dd><p>A named vector to customize column names, e.g.,
+<dd><p>A named vector to customise column names, e.g.,
 c("Database name" = "cdm_name"). The function will rename all column names
 not specified here into a tidy* format.</p></dd>
 
diff --git a/search.json b/search.json
index e3befe8..5d2fbbc 100644
--- a/search.json
+++ b/search.json
@@ -1 +1 @@
-[{"path":"https://darwin-eu.github.io/visOmopResults/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"Apache License","title":"Apache License","text":"Version 2.0, January 2004 <http://www.apache.org/licenses/>","code":""},{"path":[]},{"path":"https://darwin-eu.github.io/visOmopResults/LICENSE.html","id":"id_1-definitions","dir":"","previous_headings":"Terms and Conditions for use, reproduction, and distribution","what":"1. Definitions","title":"Apache License","text":"“License” shall mean terms conditions use, reproduction, distribution defined Sections 1 9 document. “Licensor” shall mean copyright owner entity authorized copyright owner granting License. “Legal Entity” shall mean union acting entity entities control, controlled , common control entity. purposes definition, “control” means () power, direct indirect, cause direction management entity, whether contract otherwise, (ii) ownership fifty percent (50%) outstanding shares, (iii) beneficial ownership entity. “” (“”) shall mean individual Legal Entity exercising permissions granted License. “Source” form shall mean preferred form making modifications, including limited software source code, documentation source, configuration files. “Object” form shall mean form resulting mechanical transformation translation Source form, including limited compiled object code, generated documentation, conversions media types. “Work” shall mean work authorship, whether Source Object form, made available License, indicated copyright notice included attached work (example provided Appendix ). “Derivative Works” shall mean work, whether Source Object form, based (derived ) Work editorial revisions, annotations, elaborations, modifications represent, whole, original work authorship. purposes License, Derivative Works shall include works remain separable , merely link (bind name) interfaces , Work Derivative Works thereof. “Contribution” shall mean work authorship, including original version Work modifications additions Work Derivative Works thereof, intentionally submitted Licensor inclusion Work copyright owner individual Legal Entity authorized submit behalf copyright owner. purposes definition, “submitted” means form electronic, verbal, written communication sent Licensor representatives, including limited communication electronic mailing lists, source code control systems, issue tracking systems managed , behalf , Licensor purpose discussing improving Work, excluding communication conspicuously marked otherwise designated writing copyright owner “Contribution.” “Contributor” shall mean Licensor individual Legal Entity behalf Contribution received Licensor subsequently incorporated within Work.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/LICENSE.html","id":"id_2-grant-of-copyright-license","dir":"","previous_headings":"Terms and Conditions for use, reproduction, and distribution","what":"2. Grant of Copyright License","title":"Apache License","text":"Subject terms conditions License, Contributor hereby grants perpetual, worldwide, non-exclusive, -charge, royalty-free, irrevocable copyright license reproduce, prepare Derivative Works , publicly display, publicly perform, sublicense, distribute Work Derivative Works Source Object form.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/LICENSE.html","id":"id_3-grant-of-patent-license","dir":"","previous_headings":"Terms and Conditions for use, reproduction, and distribution","what":"3. Grant of Patent License","title":"Apache License","text":"Subject terms conditions License, Contributor hereby grants perpetual, worldwide, non-exclusive, -charge, royalty-free, irrevocable (except stated section) patent license make, made, use, offer sell, sell, import, otherwise transfer Work, license applies patent claims licensable Contributor necessarily infringed Contribution(s) alone combination Contribution(s) Work Contribution(s) submitted. institute patent litigation entity (including cross-claim counterclaim lawsuit) alleging Work Contribution incorporated within Work constitutes direct contributory patent infringement, patent licenses granted License Work shall terminate date litigation filed.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/LICENSE.html","id":"id_4-redistribution","dir":"","previous_headings":"Terms and Conditions for use, reproduction, and distribution","what":"4. Redistribution","title":"Apache License","text":"may reproduce distribute copies Work Derivative Works thereof medium, without modifications, Source Object form, provided meet following conditions: () must give recipients Work Derivative Works copy License; (b) must cause modified files carry prominent notices stating changed files; (c) must retain, Source form Derivative Works distribute, copyright, patent, trademark, attribution notices Source form Work, excluding notices pertain part Derivative Works; (d) Work includes “NOTICE” text file part distribution, Derivative Works distribute must include readable copy attribution notices contained within NOTICE file, excluding notices pertain part Derivative Works, least one following places: within NOTICE text file distributed part Derivative Works; within Source form documentation, provided along Derivative Works; , within display generated Derivative Works, wherever third-party notices normally appear. contents NOTICE file informational purposes modify License. may add attribution notices within Derivative Works distribute, alongside addendum NOTICE text Work, provided additional attribution notices construed modifying License. may add copyright statement modifications may provide additional different license terms conditions use, reproduction, distribution modifications, Derivative Works whole, provided use, reproduction, distribution Work otherwise complies conditions stated License.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/LICENSE.html","id":"id_5-submission-of-contributions","dir":"","previous_headings":"Terms and Conditions for use, reproduction, and distribution","what":"5. Submission of Contributions","title":"Apache License","text":"Unless explicitly state otherwise, Contribution intentionally submitted inclusion Work Licensor shall terms conditions License, without additional terms conditions. Notwithstanding , nothing herein shall supersede modify terms separate license agreement may executed Licensor regarding Contributions.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/LICENSE.html","id":"id_6-trademarks","dir":"","previous_headings":"Terms and Conditions for use, reproduction, and distribution","what":"6. Trademarks","title":"Apache License","text":"License grant permission use trade names, trademarks, service marks, product names Licensor, except required reasonable customary use describing origin Work reproducing content NOTICE file.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/LICENSE.html","id":"id_7-disclaimer-of-warranty","dir":"","previous_headings":"Terms and Conditions for use, reproduction, and distribution","what":"7. Disclaimer of Warranty","title":"Apache License","text":"Unless required applicable law agreed writing, Licensor provides Work (Contributor provides Contributions) “” BASIS, WITHOUT WARRANTIES CONDITIONS KIND, either express implied, including, without limitation, warranties conditions TITLE, NON-INFRINGEMENT, MERCHANTABILITY, FITNESS PARTICULAR PURPOSE. solely responsible determining appropriateness using redistributing Work assume risks associated exercise permissions License.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/LICENSE.html","id":"id_8-limitation-of-liability","dir":"","previous_headings":"Terms and Conditions for use, reproduction, and distribution","what":"8. Limitation of Liability","title":"Apache License","text":"event legal theory, whether tort (including negligence), contract, otherwise, unless required applicable law (deliberate grossly negligent acts) agreed writing, shall Contributor liable damages, including direct, indirect, special, incidental, consequential damages character arising result License use inability use Work (including limited damages loss goodwill, work stoppage, computer failure malfunction, commercial damages losses), even Contributor advised possibility damages.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/LICENSE.html","id":"id_9-accepting-warranty-or-additional-liability","dir":"","previous_headings":"Terms and Conditions for use, reproduction, and distribution","what":"9. Accepting Warranty or Additional Liability","title":"Apache License","text":"redistributing Work Derivative Works thereof, may choose offer, charge fee , acceptance support, warranty, indemnity, liability obligations /rights consistent License. However, accepting obligations, may act behalf sole responsibility, behalf Contributor, agree indemnify, defend, hold Contributor harmless liability incurred , claims asserted , Contributor reason accepting warranty additional liability. END TERMS CONDITIONS","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/LICENSE.html","id":"appendix-how-to-apply-the-apache-license-to-your-work","dir":"","previous_headings":"","what":"APPENDIX: How to apply the Apache License to your work","title":"Apache License","text":"apply Apache License work, attach following boilerplate notice, fields enclosed brackets [] replaced identifying information. (Don’t include brackets!) text enclosed appropriate comment syntax file format. also recommend file class name description purpose included “printed page” copyright notice easier identification within third-party archives.","code":"Copyright [yyyy] [name of copyright owner]  Licensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at    http://www.apache.org/licenses/LICENSE-2.0  Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License."},{"path":"https://darwin-eu.github.io/visOmopResults/articles/plots.html","id":"plotting-with-a-summarised_result","dir":"Articles","previous_headings":"","what":"Plotting with a <summarised_result>","title":"Plotting tools","text":"purpose vignette turn summarise dataset penguins palmerpenguins package using PatientProfiles::summariseResult()","code":"library(PatientProfiles) library(palmerpenguins) library(dplyr) #>  #> Attaching package: 'dplyr' #> The following objects are masked from 'package:stats': #>  #>     filter, lag #> The following objects are masked from 'package:base': #>  #>     intersect, setdiff, setequal, union  summariseIsland <- function(island) {   penguins |>     filter(.data$island == .env$island) |>     summariseResult(       group = \"species\",       includeOverallGroup = TRUE,       strata = list(\"year\", \"sex\", c(\"year\", \"sex\")),       variables = c(         \"bill_length_mm\", \"bill_depth_mm\", \"flipper_length_mm\", \"body_mass_g\",          \"sex\"),       estimates = c(         \"median\", \"q25\", \"q75\", \"min\", \"max\", \"count_missing\", \"count\",          \"percentage\", \"density\")     ) |>     suppressMessages() |>     mutate(cdm_name = island) }  penguinsSummary <- bind(   summariseIsland(\"Torgersen\"),    summariseIsland(\"Biscoe\"),    summariseIsland(\"Dream\") )"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/plots.html","id":"plotting-principles","dir":"Articles","previous_headings":"Plotting with a <summarised_result>","what":"Plotting principles","title":"Plotting tools","text":"Although input visOmopResult plot function can <summarised_result> referring inputs, use columns shown tidy format: column names seen <summarised_result> format: ’s important thing aware , otherwise populating arguments becomes bit tricky. always subset <summarised_result> variable_name interest calling plotting functions. advised combine results different variables don’t share common estimates want plot tidy form NAs created.","code":"tidyColumns(penguinsSummary) #>  [1] \"cdm_name\"       \"species\"        \"year\"           \"sex\"            #>  [5] \"variable_name\"  \"variable_level\" \"count\"          \"median\"         #>  [9] \"q25\"            \"q75\"            \"min\"            \"max\"            #> [13] \"count_missing\"  \"density_x\"      \"density_y\"      \"percentage\" colnames(penguinsSummary) #>  [1] \"result_id\"        \"cdm_name\"         \"group_name\"       \"group_level\"      #>  [5] \"strata_name\"      \"strata_level\"     \"variable_name\"    \"variable_level\"   #>  [9] \"estimate_name\"    \"estimate_type\"    \"estimate_value\"   \"additional_name\"  #> [13] \"additional_level\""},{"path":"https://darwin-eu.github.io/visOmopResults/articles/plots.html","id":"scatter-plot","dir":"Articles","previous_headings":"Plotting with a <summarised_result>","what":"Scatter plot","title":"Plotting tools","text":"can create simple scatter plots using plotScatter() let’s see examples:  Additionally, can use function themeVisOmop() change default ggplot2 style default style. , can use standard ggplot2 functionalities returned plot:","code":"penguinsSummary |>   filter(variable_name == \"bill_depth_mm\") |>   filterStrata(year != \"overall\", sex == \"overall\") |>   scatterPlot(     x = \"year\",      y = \"median\",     line = TRUE,      point = TRUE,     ribbon = FALSE,     facet = \"cdm_name\",     colour = \"species\"   ) penguinsSummary |>   filter(variable_name %in% c(\"bill_length_mm\", \"bill_depth_mm\"))|>   filterStrata(year == \"overall\", sex == \"overall\") |>   filterGroup(species != \"overall\") |>   scatterPlot(     x = \"density_x\",      y = \"density_y\",     line = TRUE,      point = FALSE,     ribbon = FALSE,     facet = cdm_name ~ variable_name,     colour = \"species\"   ) +   themeVisOmop() +   ggplot2::facet_grid(cdm_name ~ variable_name, scales = \"free_x\") penguinsSummary |>   filter(variable_name == \"flipper_length_mm\") |>   filterStrata(year != \"overall\", sex %in% c(\"female\", \"male\")) |>   scatterPlot(     x = c(\"year\", \"sex\"),      y = \"median\",     ymin = \"q25\",     ymax = \"q75\",     line = FALSE,      point = TRUE,     ribbon = FALSE,     facet = cdm_name ~ species,     colour = \"sex\",     group = c(\"year\", \"sex\")   )  +   themeVisOmop(fontsizeRef = 10, legendPosition = \"top\") +   ggplot2::coord_flip() +   ggplot2::labs(y = \"Flipper length (mm)\") penguinsSummary |>   filter(variable_name %in% c(     \"flipper_length_mm\", \"bill_length_mm\", \"bill_depth_mm\")) |>   filterStrata(sex == \"overall\") |>   scatterPlot(     x = \"year\",      y = \"median\",     ymin = \"min\",     ymax = \"max\",     line = FALSE,      point = TRUE,     ribbon = TRUE,     facet = cdm_name ~ species,     colour = \"variable_name\",     group = c(\"variable_name\")   ) +   themeVisOmop(     fontsizeRef = 10,     legendPosition = \"top\"   )"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/plots.html","id":"bar-plot","dir":"Articles","previous_headings":"Plotting with a <summarised_result>","what":"Bar plot","title":"Plotting tools","text":"Let’s create simple bar plots:","code":"penguinsSummary |>   filter(variable_name == \"number records\") |>   filterGroup(species != \"overall\") |>   filterStrata(sex != \"overall\", year != \"overall\") |>   barPlot(     x = \"year\",     y = \"count\",     colour = \"sex\",     facet = cdm_name ~ species   ) +   themeVisOmop()"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/plots.html","id":"box-plot","dir":"Articles","previous_headings":"Plotting with a <summarised_result>","what":"Box plot","title":"Plotting tools","text":"Let’s create box plots body mass:  can specify want facet using formula:  Arguments ~ specify rows, arguments columns, see another example faceting also sex columns. case colouring year:  Note didnt specify x levels x axis, box plots produced anyway.","code":"penguinsSummary |>   filter(variable_name == \"body_mass_g\") |>   boxPlot(x = \"year\", facet = c(\"cdm_name\", \"species\"), colour = \"sex\") +   themeVisOmop(fontsizeRef = 10) penguinsSummary |>   filter(variable_name == \"body_mass_g\") |>   boxPlot(x = \"year\", facet = cdm_name ~ species, colour = \"sex\") +   themeVisOmop(fontsizeRef = 10, legendPosition = \"bottom\") penguinsSummary |>   filter(variable_name == \"body_mass_g\") |>   filterGroup(species != \"overall\") |>   filterStrata(sex %in% c(\"female\", \"male\"), year != \"overall\") |>   boxPlot(x = \"cdm_name\", facet = sex ~ species, colour = \"year\") +   themeVisOmop()"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/plots.html","id":"plotting-with-a-data-frame","dir":"Articles","previous_headings":"","what":"Plotting with a <data.frame>","title":"Plotting tools","text":"Plotting functions can also used normal <data.frame>. case use tidy format penguinsSummary. can seen normal data.frame: can custom plotting, example replicating last plot tidy format:","code":"penguinsTidy <- penguinsSummary |>   filter(!estimate_name %in% c(\"density_x\", \"density_y\")) |> # remove density for simplicity   tidy() penguinsTidy |> glimpse() #> Rows: 720 #> Columns: 14 #> $ cdm_name       <chr> \"Torgersen\", \"Torgersen\", \"Torgersen\", \"Torgersen\", \"To… #> $ species        <chr> \"overall\", \"overall\", \"overall\", \"overall\", \"overall\", … #> $ year           <chr> \"overall\", \"overall\", \"overall\", \"overall\", \"overall\", … #> $ sex            <chr> \"overall\", \"overall\", \"overall\", \"overall\", \"overall\", … #> $ variable_name  <chr> \"number records\", \"bill_length_mm\", \"bill_depth_mm\", \"f… #> $ variable_level <chr> NA, NA, NA, NA, NA, \"female\", \"male\", NA, NA, NA, NA, N… #> $ count          <int> 52, NA, NA, NA, NA, 24, 23, 5, 20, 16, 16, NA, NA, NA, … #> $ median         <int> NA, 38, 18, 191, 3700, NA, NA, NA, NA, NA, NA, 38, 38, … #> $ q25            <int> NA, 36, 17, 187, 3338, NA, NA, NA, NA, NA, NA, 37, 35, … #> $ q75            <int> NA, 41, 19, 195, 4000, NA, NA, NA, NA, NA, NA, 39, 41, … #> $ min            <int> NA, 33, 15, 176, 2900, NA, NA, NA, NA, NA, NA, 34, 33, … #> $ max            <int> NA, 46, 21, 210, 4700, NA, NA, NA, NA, NA, NA, 46, 45, … #> $ count_missing  <int> NA, 1, 1, 1, 1, NA, NA, NA, NA, NA, NA, 1, 0, 0, 1, 0, … #> $ percentage     <dbl> NA, NA, NA, NA, NA, 46.153846, 44.230769, 9.615385, NA,… penguinsTidy |> class() #> [1] \"tbl_df\"     \"tbl\"        \"data.frame\" penguinsTidy |>   filter(     variable_name == \"body_mass_g\",     species != \"overall\",     sex %in% c(\"female\", \"male\"),     year != \"overall\"   ) |>   boxPlot(x = \"cdm_name\", facet = ~ species + sex, colour = \"year\") +   themeVisOmop(fontsizeRef = 12)"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/plots.html","id":"custom-plotting","dir":"Articles","previous_headings":"","what":"Custom plotting","title":"Plotting tools","text":"tidy format useful apply custom ggplot2 function may interested :","code":"library(ggplot2) penguinsSummary |>   filter(variable_name == \"number records\") |>   tidy() |>   ggplot(aes(x = year, y = sex, fill = count, label = count)) +   themeVisOmop(fontsizeRef = 10) +   geom_tile() +   scale_fill_viridis_c(trans = \"log\") +    geom_text() +   facet_grid(cdm_name ~ species)"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/plots.html","id":"combine-with-ggplot2","dir":"Articles","previous_headings":"","what":"Combine with ggplot2","title":"Plotting tools","text":"plotting functions wrapper around ggplot2 package, outputs plotting functions can later customised ggplot2 similar tools. example can use ggplot2::labs() change labels ggplot2::theme() move location legend.  can also use ggplot2::ggsave() later save one plots ‘.png’ file.","code":"penguinsSummary |>   filter(     group_level != \"overall\",     strata_name == \"year &&& sex\",     !grepl(\"NA\", strata_level),     variable_name == \"body_mass_g\") |>   boxPlot(x = \"species\", facet = cdm_name ~ sex, colour = \"year\") +   themeVisOmop(legendPosition = \"top\") +   ylim(c(0, 6500)) +   labs(x = \"My custom x label\") ggsave(   \"figure8.png\", plot = last_plot(), device = \"png\", width = 15, height = 12,    units = \"cm\", dpi = 300)"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/plots.html","id":"combine-with-plotly","dir":"Articles","previous_headings":"","what":"Combine with plotly","title":"Plotting tools","text":"Although package currently provide plotly functionality ggplots can easily converted <plotly> ones using function plotly::ggplotly(). can make interactivity plots better.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/articles/tables.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"Formatting tables","text":"visOmopResults package provides user-friendly tools creating well-formatted tables plots publication-ready. vignette, focus specifically table formatting functionalities. package supports three table formats: <tibble>, <gt>, <flextable>. <tibble> <data.frame> R object, <gt> <flextable> designed create publication-ready tables can exported different formats (e.g., PNG, Word, PDF, HTML) used ShinyApps, RMarkdown, Quarto, . Although primary aim package simplify handling <summarised_result> class (see omopgenerics details), functionalities can applied <data.frame> certain requirements met.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/articles/tables.html","id":"types-of-table-functions","dir":"Articles","previous_headings":"Introduction","what":"Types of Table Functions","title":"Formatting tables","text":"two main categories table functions package: Main Table Functions: Comprehensive functions like visOmopTable() visTable() allow users fully format tables, including specifying headers, grouping columns, customizing styles. Additional Table Formatting Functions: format function set provides granular control specific table elements, enabling advanced customization beyond main functions. vignette guide usage functions.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/articles/tables.html","id":"main-functions","dir":"Articles","previous_headings":"","what":"Main Functions","title":"Formatting tables","text":"functions built top format functions, providing quick straightforward way format tables.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/articles/tables.html","id":"vistable","dir":"Articles","previous_headings":"Main Functions","what":"visTable()","title":"Formatting tables","text":"visTable() flexible function designed format <data.frame>. Let’s demonstrate usage dataset palmerpenguins package. can format data <gt> table using visTable() follows: use arguments estimateName header, <data.frame> must estimates arranged three columns: estimate_name, estimate_type, estimate_value. Let’s reshape example dataset accordingly demonstrate creating <flextable> object: Sex Estimate name Species Adelie Gentoo Chinstrap Island Biscoe Torgersen Dream Biscoe Dream female   Bill length (mm) 36.64 36.61 36.27 45.30 46.00  Bill depth (mm) 17.22 17.40 17.79 14.13 17.30  Flipper length (mm) 186.56 190.00 189.00 213.00 192.67 male   Bill length (mm) 40.76 40.92 40.11 48.54 51.40  Bill depth (mm) 19.03 18.84 18.89 15.70 19.60  Flipper length (mm) 192.56 193.50 195.00 222.09 202.78","code":"library(visOmopResults) library(palmerpenguins) library(dplyr) library(tidyr) x <- penguins |>    filter(!is.na(sex) & year == 2008) |>    select(!\"body_mass_g\") |>   summarise(across(ends_with(\"mm\"), ~mean(.x)), .by = c(\"species\", \"island\", \"sex\")) head(x) #> # A tibble: 6 × 6 #>   species island    sex    bill_length_mm bill_depth_mm flipper_length_mm #>   <fct>   <fct>     <fct>           <dbl>         <dbl>             <dbl> #> 1 Adelie  Biscoe    female           36.6          17.2              187. #> 2 Adelie  Biscoe    male             40.8          19.0              193. #> 3 Adelie  Torgersen female           36.6          17.4              190  #> 4 Adelie  Torgersen male             40.9          18.8              194. #> 5 Adelie  Dream     female           36.3          17.8              189  #> 6 Adelie  Dream     male             40.1          18.9              195 visTable(   result = x,   groupColumn = c(\"sex\"),   rename = c(\"Bill length (mm)\" = \"bill_length_mm\",              \"Bill depth (mm)\" = \"bill_depth_mm\",              \"Flipper length (mm)\" = \"flipper_length_mm\",              \"Body mass (g)\" = \"body_mass_g\"),   type = \"gt\",   hide = \"year\" ) # Transforming the dataset to include estimate columns x <- x |>   pivot_longer(     cols = ends_with(\"_mm\"),      names_to = \"estimate_name\",      values_to = \"estimate_value\"   ) |>   mutate(estimate_type = \"numeric\")  # Creating a formatted flextable visTable(   result = x,   estimateName = c(     \"Bill length (mm)\" = \"<bill_length_mm>\",     \"Bill depth (mm)\" = \"<bill_depth_mm>\",     \"Flipper length (mm)\" = \"<flipper_length_mm>\"   ),   header = c(\"species\", \"island\"),   groupColumn = \"sex\",   type = \"flextable\",   hide = c(\"year\", \"estimate_type\") )"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/tables.html","id":"visomoptable","dir":"Articles","previous_headings":"Main Functions","what":"visOmopTable()","title":"Formatting tables","text":"visOmopTable() extends functionality visTable() additional features tailored specifically handling <summarised_result> objects, making easier work standardized result formats. Let’s demonstrate visOmopTable() mock <summarised_result>: workflow quite similar visTable(), includes specific enhancements <summarised_result> objects: Automatic splitting: result object always processed using splitAll() function. Thereby, column names use arguments must based split result. settingsColumn argument: Use argument specify settings displayed main table. columns specified can also referenced arguments header, rename, groupColumn. header argument: accepts specific <summarised_result> inputs, addition typical usage visTable(). example, use “strata” header display variables strata_name, use “settings” show settings specified settingsColumns. Hidden columns: result_id estimate_type columns always hidden serve helper columns internal processes. Suppressed estimates: result object processed suppress(), obscured estimates can displayed default na value “<{minCellCount}” corresponding minimum count value used. can controlled using showMinCellCount argument. next example, visOmopTable() generates <gt> table displaying suppressed estimates (counts 1,000,000) specified minimum cell count.","code":"# Creating a mock summarised result result <- mockSummarisedResult() |>   filter(strata_name == \"age_group &&& sex\")  # Displaying the first few rows head(result) #> # A tibble: 6 × 13 #>   result_id cdm_name group_name  group_level strata_name       strata_level    #>       <int> <chr>    <chr>       <chr>       <chr>             <chr>           #> 1         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Male    #> 2         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Male   #> 3         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Female  #> 4         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Female #> 5         1 mock     cohort_name cohort2     age_group &&& sex <40 &&& Male    #> 6         1 mock     cohort_name cohort2     age_group &&& sex >=40 &&& Male   #> # ℹ 7 more variables: variable_name <chr>, variable_level <chr>, #> #   estimate_name <chr>, estimate_type <chr>, estimate_value <chr>, #> #   additional_name <chr>, additional_level <chr>  # Creating a formatted gt table visOmopTable(   result = result,   estimateName = c(     \"N%\" = \"<count> (<percentage>)\",     \"N\" = \"<count>\",     \"Mean (SD)\" = \"<mean> (<sd>)\"   ),   header = c(\"package_name\", \"age_group\"),   groupColumn = c(\"cohort_name\", \"sex\"),   settingsColumn = \"package_name\",   type = \"gt\" ) result |>   suppress(minCellCount = 1000000) |>   visOmopTable(     estimateName = c(       \"N%\" = \"<count> (<percentage>)\",       \"N\" = \"<count>\",       \"Mean (SD)\" = \"<mean> (<sd>)\"     ),     header = c(\"My visOmopTable\", \"group\"),     groupColumn = c(\"strata\"),     hide = c(\"cdm_name\"),     showMinCellCount = TRUE,     type = \"gt\"   )"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/tables.html","id":"styling-tables","dir":"Articles","previous_headings":"Main Functions","what":"Styling tables","title":"Formatting tables","text":"Tables displayed visOmopResults() follow default style, customization possible .options argument. argument allows users modify various formatting aspects using options format functions (see format Functions section learn ). table details format function styling option belongs , along description option: view default .options settings used vis tables, use following function:","code":"tableOptions() #> $decimals #>    integer percentage    numeric proportion  #>          0          2          2          2  #>  #> $decimalMark #> [1] \".\" #>  #> $bigMark #> [1] \",\" #>  #> $keepNotFormatted #> [1] TRUE #>  #> $useFormatOrder #> [1] TRUE #>  #> $delim #> [1] \"\\n\" #>  #> $includeHeaderName #> [1] TRUE #>  #> $includeHeaderKey #> [1] TRUE #>  #> $style #> [1] \"default\" #>  #> $na #> [1] \"-\" #>  #> $title #> NULL #>  #> $subtitle #> NULL #>  #> $caption #> NULL #>  #> $groupAsColumn #> [1] FALSE #>  #> $groupOrder #> NULL #>  #> $merge #> [1] \"all_columns\""},{"path":"https://darwin-eu.github.io/visOmopResults/articles/tables.html","id":"styling-gt-and-flextable","dir":"Articles","previous_headings":"Main Functions > Styling tables","what":"Styling <gt> and <flextable>","title":"Formatting tables","text":"inspect code default styles <gt> <flextable>, use functions:","code":"tableStyle(type = \"gt\") #> list(header = list(gt::cell_fill(color = \"#c8c8c8\"), gt::cell_text(weight = \"bold\",  #>     align = \"center\")), header_name = list(gt::cell_fill(color = \"#d9d9d9\"),  #>     gt::cell_text(weight = \"bold\", align = \"center\")), header_level = list(gt::cell_fill(color = \"#e1e1e1\"),  #>     gt::cell_text(weight = \"bold\", align = \"center\")), column_name = list(gt::cell_text(weight = \"bold\",  #>     align = \"center\")), group_label = list(gt::cell_fill(color = \"#e9e9e9\"),  #>     gt::cell_text(weight = \"bold\")), title = list(gt::cell_text(weight = \"bold\",  #>     size = 15, align = \"center\")), subtitle = list(gt::cell_text(weight = \"bold\",  #>     size = 12, align = \"center\")), body = list())  tableStyle(type = \"flextable\") #> list(header = list(cell = officer::fp_cell(background.color = \"#c8c8c8\"),  #>     text = officer::fp_text(bold = TRUE)), header_name = list(cell = officer::fp_cell(background.color = \"#d9d9d9\"),  #>     text = officer::fp_text(bold = TRUE)), header_level = list(cell = officer::fp_cell(background.color = \"#e1e1e1\"),  #>     text = officer::fp_text(bold = TRUE)), column_name = list(text = officer::fp_text(bold = TRUE)),  #>     group_label = list(cell = officer::fp_cell(background.color = \"#e9e9e9\",  #>         border = officer::fp_border(color = \"gray\")), text = officer::fp_text(bold = TRUE)),  #>     title = list(text = officer::fp_text(bold = TRUE, font.size = 15)),  #>     subtitle = list(text = officer::fp_text(bold = TRUE, font.size = 12)),  #>     body = list())"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/tables.html","id":"format-functions","dir":"Articles","previous_headings":"","what":"format Functions","title":"Formatting tables","text":"format set functions can used pipeline transform format <data.frame> <summarised_result> object. , ’ll demonstrate utilize functions step--step manner.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/articles/tables.html","id":"format-estimates","dir":"Articles","previous_headings":"format Functions","what":"1) Format Estimates","title":"Formatting tables","text":"formatEstimateName() formatEstimateValue() functions enable customize naming display estimates table. illustrate usage, ’ll continue result dataset. Let’s first take look estimates formatting applied:","code":"result |>    filterGroup(cohort_name == \"cohort1\") |>  # visOmopResult filter function   filterStrata(age_group == \"<40\", sex == \"Female\") |>  # visOmopResult filter function   select(variable_name, variable_level, estimate_name, estimate_type, estimate_value) #> # A tibble: 7 × 5 #>   variable_name   variable_level estimate_name estimate_type estimate_value   #>   <chr>           <chr>          <chr>         <chr>         <chr>            #> 1 number subjects NA             count         integer       1956698          #> 2 age             NA             mean          numeric       63.6465614894405 #> 3 age             NA             sd            numeric       3.15241752425209 #> 4 Medications     Amoxiciline    count         integer       27860            #> 5 Medications     Amoxiciline    percentage    percentage    21.3172711199149 #> 6 Medications     Ibuprofen      count         integer       66887            #> 7 Medications     Ibuprofen      percentage    percentage    91.8803214561194"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/tables.html","id":"estimate-values","dir":"Articles","previous_headings":"format Functions > 1) Format Estimates","what":"1.1) Estimate values","title":"Formatting tables","text":"formatEstimateValue() function allows specify number decimals different estimate_types estimate_names, well customize decimal thousand separators. Let’s see previous estimates updated afterwars: can see, estimates now reflect specified formatting rules.","code":"# Formatting estimate values result <- result |>   formatEstimateValue(     decimals = c(integer = 0, numeric = 4, percentage = 2),     decimalMark = \".\",     bigMark = \",\"   )  # Displaying the formatted subset result |>    filterGroup(cohort_name == \"cohort1\") |>     filterStrata(age_group == \"<40\", sex == \"Female\") |>    select(variable_name, variable_level, estimate_name, estimate_type, estimate_value) #> # A tibble: 7 × 5 #>   variable_name   variable_level estimate_name estimate_type estimate_value #>   <chr>           <chr>          <chr>         <chr>         <chr>          #> 1 number subjects NA             count         integer       1,956,698      #> 2 age             NA             mean          numeric       63.6466        #> 3 age             NA             sd            numeric       3.1524         #> 4 Medications     Amoxiciline    count         integer       27,860         #> 5 Medications     Amoxiciline    percentage    percentage    21.32          #> 6 Medications     Ibuprofen      count         integer       66,887         #> 7 Medications     Ibuprofen      percentage    percentage    91.88"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/tables.html","id":"estimate-names","dir":"Articles","previous_headings":"format Functions > 1) Format Estimates","what":"1.2) Estimate names","title":"Formatting tables","text":"Next, format estimate names using formatEstimateName() function. function allows us combine counts percentages “N (%)”, among estimate combinations Now, estimate names displayed specified, “N (%)” counts percentages. keepNotFormatted argument ensures unformatted rows remain dataset, useFormatOrder allows control display order estimates.","code":"# Formatting estimate names result <- result |>    formatEstimateName(     estimateName = c(       \"N (%)\" = \"<count> (<percentage>%)\",        \"N\" = \"<count>\",       \"Mean (SD)\" = \"<mean> (<sd>)\"     ),     keepNotFormatted = TRUE,     useFormatOrder = FALSE   )  # Displaying the formatted subset with new estimate names result |>    filterGroup(cohort_name == \"cohort1\") |>     filterStrata(age_group == \"<40\", sex == \"Female\") |>    select(variable_name, variable_level, estimate_name, estimate_type, estimate_value) #> # A tibble: 4 × 5 #>   variable_name   variable_level estimate_name estimate_type estimate_value   #>   <chr>           <chr>          <chr>         <chr>         <chr>            #> 1 number subjects NA             N             character     1,956,698        #> 2 age             NA             Mean (SD)     character     63.6466 (3.1524) #> 3 Medications     Amoxiciline    N (%)         character     27,860 (21.32%)  #> 4 Medications     Ibuprofen      N (%)         character     66,887 (91.88%)"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/tables.html","id":"format-header","dir":"Articles","previous_headings":"format Functions","what":"2) Format Header","title":"Formatting tables","text":"formatHeader() used create complex multi-level headers tables, making easy present grouped data clearly.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/articles/tables.html","id":"header-levels","dir":"Articles","previous_headings":"format Functions > 2) Format Header","what":"Header levels","title":"Formatting tables","text":"3 different levels headers, identified following keys: header: Custom labels correspond column names table values. header_name: Labels derived column names. Can omitted includeHeaderName =  FALSE. header_level: Labels derived values within columns set header. keys, together delimiter header levels (delim) used formatTable() format style gt flextable tables. Let’s create multi-level header strata columns, including three keys. show column names transformed: table formatting, won’t include header_name labels. Let’s see looks exclude :","code":"result |>   mutate(across(c(\"strata_name\", \"strata_level\"), ~ gsub(\"&&&\", \"and\", .x))) |>   formatHeader(     header = c(\"Stratifications\", \"strata_name\", \"strata_level\"),     delim = \"\\n\",     includeHeaderName = TRUE,     includeHeaderKey = TRUE   ) |>    colnames() #>  [1] \"result_id\"                                                                                                                                    #>  [2] \"cdm_name\"                                                                                                                                     #>  [3] \"group_name\"                                                                                                                                   #>  [4] \"group_level\"                                                                                                                                  #>  [5] \"variable_name\"                                                                                                                                #>  [6] \"variable_level\"                                                                                                                               #>  [7] \"estimate_name\"                                                                                                                                #>  [8] \"estimate_type\"                                                                                                                                #>  [9] \"additional_name\"                                                                                                                              #> [10] \"additional_level\"                                                                                                                             #> [11] \"[header]Stratifications\\n[header_name]strata_name\\n[header_level]age_group and sex\\n[header_name]strata_level\\n[header_level]<40 and Male\"    #> [12] \"[header]Stratifications\\n[header_name]strata_name\\n[header_level]age_group and sex\\n[header_name]strata_level\\n[header_level]>=40 and Male\"   #> [13] \"[header]Stratifications\\n[header_name]strata_name\\n[header_level]age_group and sex\\n[header_name]strata_level\\n[header_level]<40 and Female\"  #> [14] \"[header]Stratifications\\n[header_name]strata_name\\n[header_level]age_group and sex\\n[header_name]strata_level\\n[header_level]>=40 and Female\" result <- result |>   mutate(across(c(\"strata_name\", \"strata_level\"), ~ gsub(\"&&&\", \"and\", .x))) |>   formatHeader(     header = c(\"Stratifications\", \"strata_name\", \"strata_level\"),     delim = \"\\n\",     includeHeaderName = FALSE,     includeHeaderKey = TRUE   )    colnames(result) #>  [1] \"result_id\"                                                                               #>  [2] \"cdm_name\"                                                                                #>  [3] \"group_name\"                                                                              #>  [4] \"group_level\"                                                                             #>  [5] \"variable_name\"                                                                           #>  [6] \"variable_level\"                                                                          #>  [7] \"estimate_name\"                                                                           #>  [8] \"estimate_type\"                                                                           #>  [9] \"additional_name\"                                                                         #> [10] \"additional_level\"                                                                        #> [11] \"[header]Stratifications\\n[header_level]age_group and sex\\n[header_level]<40 and Male\"    #> [12] \"[header]Stratifications\\n[header_level]age_group and sex\\n[header_level]>=40 and Male\"   #> [13] \"[header]Stratifications\\n[header_level]age_group and sex\\n[header_level]<40 and Female\"  #> [14] \"[header]Stratifications\\n[header_level]age_group and sex\\n[header_level]>=40 and Female\""},{"path":"https://darwin-eu.github.io/visOmopResults/articles/tables.html","id":"format-table","dir":"Articles","previous_headings":"format Functions","what":"3) Format Table","title":"Formatting tables","text":"formatTable() function final step formatting pipeline, formatted <data.frame> converted either <gt> <flextable>.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/articles/tables.html","id":"prepare-data","dir":"Articles","previous_headings":"format Functions > 3) Format Table","what":"Prepare data","title":"Formatting tables","text":"using formatTable(), ’ll tidy <data.frame> splitting group additional name-level columns (see vignette tidying <summarised_result>), drop unwanted columns:","code":"result <- result |>   splitGroup() |>   splitAdditional() |>   select(!c(\"result_id\", \"estimate_type\", \"cdm_name\")) head(result) #> # A tibble: 6 × 8 #>   cohort_name variable_name  variable_level estimate_name [header]Stratificati…¹ #>   <chr>       <chr>          <chr>          <chr>         <chr>                  #> 1 cohort1     number subjec… NA             N             3,203,857              #> 2 cohort2     number subjec… NA             N             7,353,196              #> 3 cohort1     age            NA             Mean (SD)     22.5563 (3.8918)       #> 4 cohort2     age            NA             Mean (SD)     68.0163 (0.6522)       #> 5 cohort1     Medications    Amoxiciline    N (%)         54,248 (92.00%)        #> 6 cohort2     Medications    Amoxiciline    N (%)         37,697 (71.83%)        #> # ℹ abbreviated name: #> #   ¹​`[header]Stratifications\\n[header_level]age_group and sex\\n[header_level]<40 and Male` #> # ℹ 3 more variables: #> #   `[header]Stratifications\\n[header_level]age_group and sex\\n[header_level]>=40 and Male` <chr>, #> #   `[header]Stratifications\\n[header_level]age_group and sex\\n[header_level]<40 and Female` <chr>, #> #   `[header]Stratifications\\n[header_level]age_group and sex\\n[header_level]>=40 and Female` <chr>"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/tables.html","id":"use-formattable","dir":"Articles","previous_headings":"format Functions > 3) Format Table","what":"Use formatTable()","title":"Formatting tables","text":"Now data cleaned organized, formatTable() can used create well-structured <gt> <flextable> object. examples , used default style defined visOmopResults package (use gtStyle() flextableStyle() see styles). However, ’s possible customize appearance different parts table better suit needs.","code":"result |>   formatTable(     type = \"gt\",     delim = \"\\n\",     style = \"default\",     na = \"-\",     title = \"My formatted table!\",     subtitle = \"Created with the `visOmopResults` R package.\",     caption = NULL,     groupColumn = \"cohort_name\",     groupAsColumn = FALSE,     groupOrder = c(\"cohort2\", \"cohort1\"),     merge = \"variable_name\"   )"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/tables.html","id":"customizing-table-styles","dir":"Articles","previous_headings":"format Functions > 3) Format Table","what":"Customizing Table Styles","title":"Formatting tables","text":"Let’s start applying custom style <gt> table: creating similarly styled <flextable>, office R package required access specific formatting functions. formatted table! Created `visOmopResults` R package. cohort_name variable_name variable_level estimate_name Stratifications age_group sex <40 Male >=40 Male <40 Female >=40 Female cohort2   number subjects - N 7,353,196 1,959,567 9,805,397 7,415,215  age - Mean (SD) 68.0163 (0.6522) 49.8846 (3.5421) 64.1679 (8.2520) 66.0284 (2.7382)  Medications Amoxiciline N (%) 37,697 (71.83%) 55,991 (24.13%) 85,708 (54.70%) 38,481 (83.48%)   Ibuprofen N (%) 1,148 (16.46%) 88,825 (66.32%) 99,635 (85.66%) 50,019 (92.65%) cohort1   number subjects - N 3,203,857 4,023,282 1,956,698 4,035,381  age - Mean (SD) 22.5563 (3.8918) 30.0831 (4.6119) 63.6466 (3.1524) 47.9025 (1.7468)  Medications Amoxiciline N (%) 54,248 (92.00%) 54,460 (40.07%) 27,860 (21.32%) 44,670 (67.18%)   Ibuprofen N (%) 21,843 (56.69%) 41,836 (25.30%) 66,887 (91.88%) 50,765 (86.74%)","code":"result |>   formatTable(     type = \"gt\",     delim = \"\\n\",     style = list(       \"header\" = list(gt::cell_text(weight = \"bold\"),                        gt::cell_fill(color = \"orange\")),       \"header_level\" = list(gt::cell_text(weight = \"bold\"),                        gt::cell_fill(color = \"yellow\")),       \"column_name\" = gt::cell_text(weight = \"bold\"),       \"group_label\" = list(gt::cell_fill(color = \"blue\"),                            gt::cell_text(color = \"white\", weight = \"bold\")),       \"title\" = list(gt::cell_text(size = 20, weight = \"bold\")),       \"subtitle\" = list(gt::cell_text(size = 15)),       \"body\" = gt::cell_text(color = \"red\")     ),     na = \"-\",     title = \"My formatted table!\",     subtitle = \"Created with the `visOmopResults` R package.\",     caption = NULL,     groupColumn = \"cohort_name\",     groupAsColumn = FALSE,     groupOrder = c(\"cohort2\", \"cohort1\"),     merge = \"variable_name\"   ) result |>   formatTable(     type = \"flextable\",     delim = \"\\n\",     style = list(       \"header\" = list(         \"cell\" = officer::fp_cell(background.color = \"orange\"),         \"text\" = officer::fp_text(bold = TRUE)),       \"header_level\" = list(         \"cell\" = officer::fp_cell(background.color = \"yellow\"),         \"text\" = officer::fp_text(bold = TRUE)),       \"column_name\" = list(\"text\" = officer::fp_text(bold = TRUE)),       \"group_label\" = list(         \"cell\" = officer::fp_cell(background.color = \"blue\"),         \"text\" = officer::fp_text(bold = TRUE, color = \"white\")),       \"title\" = list(\"text\" = officer::fp_text(bold = TRUE, font.size = 20)),       \"subtitle\" = list(\"text\" = officer::fp_text(font.size = 15)),       \"body\" = list(\"text\" = officer::fp_text(color = \"red\"))     ),     na = \"-\",     title = \"My formatted table!\",     subtitle = \"Created with the `visOmopResults` R package.\",     caption = NULL,     groupColumn = \"cohort_name\",     groupAsColumn = FALSE,     groupOrder = c(\"cohort2\", \"cohort1\"),     merge = \"variable_name\"   )"},{"path":"https://darwin-eu.github.io/visOmopResults/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Martí Català. Author. Núria Mercadé-Besora. Author, maintainer. Yuchen Guo. Contributor. Elin Rowlands. Contributor. Edward Burn. Contributor.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Català M, Mercadé-Besora N (2025). visOmopResults: Graphs Tables OMOP Results. R package version 0.5.1, https://github.com/darwin-eu/visOmopResults, https://darwin-eu.github.io/visOmopResults/.","code":"@Manual{,   title = {visOmopResults: Graphs and Tables for OMOP Results},   author = {Martí Català and Núria Mercadé-Besora},   year = {2025},   note = {R package version 0.5.1, https://github.com/darwin-eu/visOmopResults},   url = {https://darwin-eu.github.io/visOmopResults/}, }"},{"path":[]},{"path":"https://darwin-eu.github.io/visOmopResults/index.html","id":"package-overview","dir":"","previous_headings":"","what":"Package overview","title":"Graphs and Tables for OMOP Results","text":"visOmopResults offers set functions tailored format objects class <summarised_result> (defined omopgenerics package). provides functionality create formatted tables generate plots. visualizations highly versatile reporting results Shiny apps, RMarkdown, Quarto, , supporting various output formats HTML, PNG, Word, PDF.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/index.html","id":"lets-get-started","dir":"","previous_headings":"","what":"Let’s get started","title":"Graphs and Tables for OMOP Results","text":"can install latest version visOmopResults CRAN: can install development version GitHub : <summarised_result> standardised output format utilized across various packages, including: CohortCharacteristics DrugUtilisation IncidencePrevalence PatientProfiles CodelistGenerator CohortSurvival CohortSymmetry Although standard output format essential, can sometimes challenging manage. visOmopResults package aims simplify process. demonstrate package’s functionality, let’s start using mock result:","code":"install.packages(\"visOmopResults\") # install.packages(\"pak\") pak::pkg_install(\"darwin-eu/visOmopResults\") library(visOmopResults) result <- mockSummarisedResult()"},{"path":"https://darwin-eu.github.io/visOmopResults/index.html","id":"tables-visualisations","dir":"","previous_headings":"","what":"Tables visualisations","title":"Graphs and Tables for OMOP Results","text":"Currently table functionalities built around 3 packages: tibble, gt, flextable. two main functions: visOmopTable(): Creates well-formatted table specifically <summarised_result> object. visTable(): Creates nicely formatted table <data.frame> object. Let’s see simple example:","code":"result |>   visOmopTable(     type = \"flextable\",     estimateName = c(       \"N(%)\" = \"<count> (<percentage>%)\",        \"N\" = \"<count>\",        \"mean (sd)\" = \"<mean> (<sd>)\"),     header = c(\"sex\"),     settingsColumn = NULL,     groupColumn = c(\"cohort_name\", \"age_group\"),     rename = c(\"Variable\" = \"variable_name\", \" \" = \"variable_level\"),     hide = \"cdm_name\"   )"},{"path":"https://darwin-eu.github.io/visOmopResults/index.html","id":"plots-visualisations","dir":"","previous_headings":"","what":"Plots visualisations","title":"Graphs and Tables for OMOP Results","text":"Currently plot functionalities built around ggplot2. output plot functions <ggplot2> object can customised. three plotting functions: plotScatter() create scatter plot. plotBar() create bar plot. plotBox() create box plot. Let’s see can create simple boxplot age using tool:","code":"library(dplyr) result |>   filter(variable_name == \"number subjects\") |>   filterStrata(sex != \"overall\") |>   barPlot(x = \"age_group\",            y = \"count\",           facet = \"cohort_name\",            colour = \"sex\")"},{"path":[]},{"path":"https://darwin-eu.github.io/visOmopResults/reference/barPlot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a bar plot visualisation from a <summarised_result> object — barPlot","text":"","code":"barPlot(   result,   x,   y,   width = NULL,   just = 0.5,   facet = NULL,   colour = NULL,   label = character() )"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/barPlot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a bar plot visualisation from a <summarised_result> object — barPlot","text":"result <summarised_result> object. x Column estimate name used x variable. y Column estimate name used y variable. width Bar width, geom_col() ggplot2 package. just Adjustment column placement, geom_col() ggplot2 package. facet Variables facet , formula can provided specify variables used rows ones columns. colour Columns use determine colors. label Character vector columns display interactively plotly.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/barPlot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a bar plot visualisation from a <summarised_result> object — barPlot","text":"plot object.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/barPlot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a bar plot visualisation from a <summarised_result> object — barPlot","text":"","code":"result <- mockSummarisedResult() |> dplyr::filter(variable_name == \"age\")  barPlot(   result = result,   x = \"cohort_name\",   y = \"mean\",   facet = c(\"age_group\", \"sex\"),   colour = \"sex\")"},{"path":[]},{"path":"https://darwin-eu.github.io/visOmopResults/reference/boxPlot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a box plot visualisation from a <summarised_result> object — boxPlot","text":"","code":"boxPlot(   result,   x,   lower = \"q25\",   middle = \"median\",   upper = \"q75\",   ymin = \"min\",   ymax = \"max\",   facet = NULL,   colour = NULL,   label = character() )"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/boxPlot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a box plot visualisation from a <summarised_result> object — boxPlot","text":"result <summarised_result> object. x Columns use x axes. lower Estimate name lower quantile box. middle Estimate name middle line box. upper Estimate name upper quantile box. ymin Estimate name lower limit bars. ymax Estimate name upper limit bars. facet Variables facet , formula can provided specify variables used rows ones columns. colour Columns use determine colors. label Character vector columns display interactively plotly.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/boxPlot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a box plot visualisation from a <summarised_result> object — boxPlot","text":"ggplot2 object.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/boxPlot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a box plot visualisation from a <summarised_result> object — boxPlot","text":"","code":"dplyr::tibble(year = \"2000\", q25 = 25, median = 50, q75 = 75, min = 0, max = 100) |>   boxPlot(x = \"year\")"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/customiseText.html","id":null,"dir":"Reference","previous_headings":"","what":"Apply styling to text or column names — customiseText","title":"Apply styling to text or column names — customiseText","text":"function styles character vectors column names data frame. styling function can customized, can provide specific replacements certain values.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/customiseText.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Apply styling to text or column names — customiseText","text":"","code":"customiseText(   x,   fun = function(x) stringr::str_to_sentence(gsub(\"_\", \" \", x)),   custom = NULL,   keep = NULL )"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/customiseText.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Apply styling to text or column names — customiseText","text":"x character vector style text. fun styling function apply text x. default function converts snake_case sentence case. custom named character vector indicating custom names specific values x. NULL, styling function fun applied values. keep Either character vector names keep unchanged. NULL, names styled.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/customiseText.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Apply styling to text or column names — customiseText","text":"character vector styled text data frame styled column names.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/customiseText.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Apply styling to text or column names — customiseText","text":"","code":"# Styling a character vector customiseText(c(\"some_column_name\", \"another_column\")) #> [1] \"Some column name\" \"Another column\"    # Custom styling for specific values customiseText(x = c(\"some_column\", \"another_column\"),           custom = c(\"Custom Name\" = \"another_column\")) #> [1] \"Some column\" \"Custom Name\"  # Keeping specific values unchanged customiseText(x = c(\"some_column\", \"another_column\"), keep = \"another_column\") #> [1] \"Some column\"    \"another_column\"  # Styling column names and variables in a data frame dplyr::tibble(   some_column = c(\"hi_there\", \"rename_me\", \"example\", \"to_keep\"),   another_column = 1:4,   to_keep = \"as_is\" ) |>   dplyr::mutate(     \"some_column\" = customiseText(some_column, custom = c(\"EXAMPLE\" = \"example\"), keep = \"to_keep\")   ) |>   dplyr::rename_with(.fn = ~ customiseText(.x, keep = \"to_keep\")) #> # A tibble: 4 × 3 #>   `Some column` `Another column` to_keep #>   <chr>                    <int> <chr>   #> 1 Hi there                     1 as_is   #> 2 Rename me                    2 as_is   #> 3 EXAMPLE                      3 as_is   #> 4 to_keep                      4 as_is"},{"path":[]},{"path":"https://darwin-eu.github.io/visOmopResults/reference/emptyTable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Returns an empty table — emptyTable","text":"","code":"emptyTable(type = \"gt\")"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/emptyTable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Returns an empty table — emptyTable","text":"type desired format output table. See tableType() allowed options.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/emptyTable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Returns an empty table — emptyTable","text":"empty table class specified type","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/emptyTable.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Returns an empty table — emptyTable","text":"Table data","code":"emptyTable(type = \"flextable\") .cl-cb9cff24{}.cl-cb95428e{font-family:'DejaVu Sans';font-size:11pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-cb993862{margin:0;text-align:right;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-cb99532e{width:1.5in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}Table has no data"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatEstimateName.html","id":null,"dir":"Reference","previous_headings":"","what":"Formats estimate_name and estimate_value column — formatEstimateName","title":"Formats estimate_name and estimate_value column — formatEstimateName","text":"Formats estimate_name estimate_value columns changing name estimate name /joining different estimates together single row.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatEstimateName.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Formats estimate_name and estimate_value column — formatEstimateName","text":"","code":"formatEstimateName(   result,   estimateName = NULL,   keepNotFormatted = TRUE,   useFormatOrder = TRUE )"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatEstimateName.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Formats estimate_name and estimate_value column — formatEstimateName","text":"result <summarised_result>. estimateName Named list estimate name's join, sorted computation order. Indicate estimate_name's <...>. keepNotFormatted Whether keep rows formatted. useFormatOrder Whether use order estimate names appear estimateName (TRUE), use order input dataframe (FALSE).","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatEstimateName.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Formats estimate_name and estimate_value column — formatEstimateName","text":"<summarised_result> object.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatEstimateName.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Formats estimate_name and estimate_value column — formatEstimateName","text":"","code":"result <- mockSummarisedResult() result |>   formatEstimateName(     estimateName = c(       \"N (%)\" = \"<count> (<percentage>%)\", \"N\" = \"<count>\"     ),     keepNotFormatted = FALSE   ) #> # A tibble: 54 × 13 #>    result_id cdm_name group_name  group_level strata_name       strata_level    #>        <int> <chr>    <chr>       <chr>       <chr>             <chr>           #>  1         1 mock     cohort_name cohort1     overall           overall         #>  2         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Male    #>  3         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Male   #>  4         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Female  #>  5         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Female #>  6         1 mock     cohort_name cohort1     sex               Male            #>  7         1 mock     cohort_name cohort1     sex               Female          #>  8         1 mock     cohort_name cohort1     age_group         <40             #>  9         1 mock     cohort_name cohort1     age_group         >=40            #> 10         1 mock     cohort_name cohort2     overall           overall         #> # ℹ 44 more rows #> # ℹ 7 more variables: variable_name <chr>, variable_level <chr>, #> #   estimate_name <chr>, estimate_type <chr>, estimate_value <chr>, #> #   additional_name <chr>, additional_level <chr>"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatEstimateValue.html","id":null,"dir":"Reference","previous_headings":"","what":"Formats the estimate_value column — formatEstimateValue","title":"Formats the estimate_value column — formatEstimateValue","text":"Formats estimate_value column <summarised_result> object editing number decimals, decimal thousand/millions separator marks.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatEstimateValue.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Formats the estimate_value column — formatEstimateValue","text":"","code":"formatEstimateValue(   result,   decimals = c(integer = 0, numeric = 2, percentage = 1, proportion = 3),   decimalMark = \".\",   bigMark = \",\" )"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatEstimateValue.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Formats the estimate_value column — formatEstimateValue","text":"result <summarised_result>. decimals Number decimals per estimate type (integer, numeric, percentage, proportion), estimate name, estimate values (introduce number decimals). decimalMark Decimal separator mark. bigMark Thousand millions separator mark.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatEstimateValue.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Formats the estimate_value column — formatEstimateValue","text":"<summarised_result>.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatEstimateValue.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Formats the estimate_value column — formatEstimateValue","text":"","code":"result <- mockSummarisedResult()  result |> formatEstimateValue(decimals = 1) #> # A tibble: 126 × 13 #>    result_id cdm_name group_name  group_level strata_name       strata_level    #>        <int> <chr>    <chr>       <chr>       <chr>             <chr>           #>  1         1 mock     cohort_name cohort1     overall           overall         #>  2         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Male    #>  3         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Male   #>  4         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Female  #>  5         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Female #>  6         1 mock     cohort_name cohort1     sex               Male            #>  7         1 mock     cohort_name cohort1     sex               Female          #>  8         1 mock     cohort_name cohort1     age_group         <40             #>  9         1 mock     cohort_name cohort1     age_group         >=40            #> 10         1 mock     cohort_name cohort2     overall           overall         #> # ℹ 116 more rows #> # ℹ 7 more variables: variable_name <chr>, variable_level <chr>, #> #   estimate_name <chr>, estimate_type <chr>, estimate_value <chr>, #> #   additional_name <chr>, additional_level <chr>  result |> formatEstimateValue(decimals = c(integer = 0, numeric = 1)) #> # A tibble: 126 × 13 #>    result_id cdm_name group_name  group_level strata_name       strata_level    #>        <int> <chr>    <chr>       <chr>       <chr>             <chr>           #>  1         1 mock     cohort_name cohort1     overall           overall         #>  2         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Male    #>  3         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Male   #>  4         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Female  #>  5         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Female #>  6         1 mock     cohort_name cohort1     sex               Male            #>  7         1 mock     cohort_name cohort1     sex               Female          #>  8         1 mock     cohort_name cohort1     age_group         <40             #>  9         1 mock     cohort_name cohort1     age_group         >=40            #> 10         1 mock     cohort_name cohort2     overall           overall         #> # ℹ 116 more rows #> # ℹ 7 more variables: variable_name <chr>, variable_level <chr>, #> #   estimate_name <chr>, estimate_type <chr>, estimate_value <chr>, #> #   additional_name <chr>, additional_level <chr>  result |>   formatEstimateValue(decimals = c(numeric = 1, count = 0)) #> # A tibble: 126 × 13 #>    result_id cdm_name group_name  group_level strata_name       strata_level    #>        <int> <chr>    <chr>       <chr>       <chr>             <chr>           #>  1         1 mock     cohort_name cohort1     overall           overall         #>  2         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Male    #>  3         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Male   #>  4         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Female  #>  5         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Female #>  6         1 mock     cohort_name cohort1     sex               Male            #>  7         1 mock     cohort_name cohort1     sex               Female          #>  8         1 mock     cohort_name cohort1     age_group         <40             #>  9         1 mock     cohort_name cohort1     age_group         >=40            #> 10         1 mock     cohort_name cohort2     overall           overall         #> # ℹ 116 more rows #> # ℹ 7 more variables: variable_name <chr>, variable_level <chr>, #> #   estimate_name <chr>, estimate_type <chr>, estimate_value <chr>, #> #   additional_name <chr>, additional_level <chr>"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatHeader.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a header for gt and flextable objects — formatHeader","title":"Create a header for gt and flextable objects — formatHeader","text":"Pivots <summarised_result> object based column names header, generating specific column names subsequent header formatting formatTable function.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatHeader.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a header for gt and flextable objects — formatHeader","text":"","code":"formatHeader(   result,   header,   delim = \"\\n\",   includeHeaderName = TRUE,   includeHeaderKey = TRUE )"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatHeader.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a header for gt and flextable objects — formatHeader","text":"result <summarised_result>. header Names variables make headers. delim Delimiter use separate headers. includeHeaderName Whether include column name header. includeHeaderKey Whether include header key (header, header_name, header_level) header type column names.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatHeader.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a header for gt and flextable objects — formatHeader","text":"tibble rows pivotted columns key names subsequent header formatting.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatHeader.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a header for gt and flextable objects — formatHeader","text":"","code":"result <- mockSummarisedResult()  result |>   formatHeader(     header = c(       \"Study cohorts\", \"group_level\", \"Study strata\", \"strata_name\",       \"strata_level\"     ),     includeHeaderName = FALSE   ) #> # A tibble: 7 × 27 #>   result_id cdm_name group_name  variable_name   variable_level estimate_name #>       <int> <chr>    <chr>       <chr>           <chr>          <chr>         #> 1         1 mock     cohort_name number subjects NA             count         #> 2         1 mock     cohort_name age             NA             mean          #> 3         1 mock     cohort_name age             NA             sd            #> 4         1 mock     cohort_name Medications     Amoxiciline    count         #> 5         1 mock     cohort_name Medications     Amoxiciline    percentage    #> 6         1 mock     cohort_name Medications     Ibuprofen      count         #> 7         1 mock     cohort_name Medications     Ibuprofen      percentage    #> # ℹ 21 more variables: estimate_type <chr>, additional_name <chr>, #> #   additional_level <chr>, #> #   `[header]Study cohorts\\n[header_level]cohort1\\n[header]Study strata\\n[header_level]overall\\n[header_level]overall` <chr>, #> #   `[header]Study cohorts\\n[header_level]cohort1\\n[header]Study strata\\n[header_level]age_group &&& sex\\n[header_level]<40 &&& Male` <chr>, #> #   `[header]Study cohorts\\n[header_level]cohort1\\n[header]Study strata\\n[header_level]age_group &&& sex\\n[header_level]>=40 &&& Male` <chr>, #> #   `[header]Study cohorts\\n[header_level]cohort1\\n[header]Study strata\\n[header_level]age_group &&& sex\\n[header_level]<40 &&& Female` <chr>, #> #   `[header]Study cohorts\\n[header_level]cohort1\\n[header]Study strata\\n[header_level]age_group &&& sex\\n[header_level]>=40 &&& Female` <chr>, …"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatTable.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a flextable or gt object from a dataframe — formatTable","title":"Creates a flextable or gt object from a dataframe — formatTable","text":"Creates flextable object dataframe using delimiter span header, allows easily customise table style.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatTable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a flextable or gt object from a dataframe — formatTable","text":"","code":"formatTable(   x,   type = \"gt\",   delim = \"\\n\",   style = \"default\",   na = \"-\",   title = NULL,   subtitle = NULL,   caption = NULL,   groupColumn = NULL,   groupAsColumn = FALSE,   groupOrder = NULL,   merge = NULL )"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatTable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a flextable or gt object from a dataframe — formatTable","text":"x dataframe. type desired format output table. See tableType() allowed options. \"tibble\", formatting applied. delim Delimiter. style Named list specifies style different parts gt flextable table generated. Accepted style entries : title, subtitle, header, header_name, header_level, column_name, group_label, body. Alternatively, use \"default\" get visOmopResults style, NULL gt/flextable style. Keep mind styling code different gt flextable. see \"deafult\" style code use tableStyle(). na display missing values. used \"datatable\". title Title table, NULL title. used \"datatable\". subtitle Subtitle table, NULL subtitle. used \"datatable\". caption Caption table, NULL caption. Text markdown formatting style (e.g. *caption * caption italics). groupColumn Specifies columns use group labels. default, new group name combination column names, joined \"_\". assign custom group name, provide named list : list(newGroupName = c(\"variable_name\", \"variable_level\")) groupAsColumn Whether display group labels column (TRUE) rows (FALSE). used \"datatable\". groupOrder Order display group labels. used \"datatable\". merge Names columns merge vertically consecutive row cells identical values. Alternatively, use \"all_columns\" apply merging columns, use NULL indicate merging. used \"datatable\".","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatTable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a flextable or gt object from a dataframe — formatTable","text":"flextable object. flextable gt object.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatTable.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a flextable or gt object from a dataframe — formatTable","text":"fxTable example group_level result_id cdm_name group_name variable_name variable_level estimate_name estimate_type additional_name additional_level Study strata overall age_group &&& sex sex age_group overall <40 &&& Male >=40 &&& Male <40 &&& Female >=40 &&& Female Male Female <40 >=40 cohort1 1 mock cohort_name number subjects -- count integer overall overall 1,333,485 9,272,818 8,941,227 2,036,644 2,569,829 6,140,056 4,414,992 3,155,947 1,013,138    age -- mean numeric overall overall 26.2 41.6 43.9 18.2 7.8 1.8 72.8 97.1 53.5      sd numeric overall overall 9.6 4.5 9.8 5.4 3.6 5.0 0.7 9.7 6.5    Medications Amoxiciline count integer overall overall 45,675 17,903 96,621 71,341 2,489 62,646 82,792 64,307 70,848      percentage percentage overall overall 0.865807477384806 43.0898792576045 72.493509715423 41.2256387062371 55.0862395204604 15.6360570108518 4.30012932047248 68.464411306195 51.4402497094125     Ibuprofen count integer overall overall 34,970 98,267 40,885 36,087 65,251 14,356 68,080 85,929 83,863      percentage percentage overall overall 11.3047500839457 97.0262279734015 64.8082781815901 5.6073043262586 47.3137095803395 29.4625013135374 61.0299621941522 12.1108880266547 62.9416507901624 cohort2 1 mock cohort_name number subjects -- count integer overall overall 2,726,462 6,536,994 9,278,701 266,247 5,594,912 8,541,737 758,830 2,058,289 4,958,896    age -- mean numeric overall overall 16.6 5.8 45.9 62.3 59.5 74.3 52.4 49.7 1.5      sd numeric overall overall 9.8 5.4 7.6 5.6 7.8 6.4 3.8 3.6 8.4    Medications Amoxiciline count integer overall overall 87,073 28,181 17,322 10,967 58,622 85,072 92,153 67,566 35,059      percentage percentage overall overall 94.568784837611 84.309694217518 6.48830933496356 76.2110914569348 7.83842522650957 13.3507662685588 80.9696201002225 55.9383239364251 73.3729686122388     Ibuprofen count integer overall overall 88,131 23,770 57,863 89,790 34,443 76,086 73,110 85,243 97,582      percentage percentage overall overall 71.1955302860588 61.2082786625251 3.44292330555618 66.5890787029639 65.2967276517302 45.1858439715579 51.6804101876915 67.6610797178 88.0933094071224","code":"# Example 1 mockSummarisedResult() |>   formatEstimateValue(decimals = c(integer = 0, numeric = 1)) |>   formatHeader(     header = c(\"Study strata\", \"strata_name\", \"strata_level\"),     includeHeaderName = FALSE   ) |>   formatTable(     type = \"flextable\",     style = \"default\",     na = \"--\",     title = \"fxTable example\",     subtitle = NULL,     caption = NULL,     groupColumn = \"group_level\",     groupAsColumn = TRUE,     groupOrder = c(\"cohort1\", \"cohort2\"),     merge = \"all_columns\"   ) .cl-cce2bd42{}.cl-ccd90cb6{font-family:'Arial';font-size:15pt;font-weight:bold;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-ccd90cca{font-family:'Arial';font-size:10pt;font-weight:bold;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-ccd90ccb{font-family:'DejaVu Sans';font-size:11pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-ccdc5dc6{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-ccdc5dd0{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-ccdc5dda{margin:0;text-align:right;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-ccdc8378{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.2pt solid rgba(190, 190, 190, 1.00);border-top: 1.2pt solid rgba(190, 190, 190, 1.00);border-left: 1.2pt solid rgba(190, 190, 190, 1.00);border-right: 1.2pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-ccdc8382{width:0.75in;background-color:rgba(200, 200, 200, 1.00);vertical-align: middle;border-bottom: 1.2pt solid rgba(190, 190, 190, 1.00);border-top: 1.2pt solid rgba(190, 190, 190, 1.00);border-left: 1.2pt solid rgba(190, 190, 190, 1.00);border-right: 1.2pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-ccdc8383{width:0.75in;background-color:rgba(225, 225, 225, 1.00);vertical-align: middle;border-bottom: 1.2pt solid rgba(190, 190, 190, 1.00);border-top: 1.2pt solid rgba(190, 190, 190, 1.00);border-left: 1.2pt solid rgba(190, 190, 190, 1.00);border-right: 1.2pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-ccdc8384{width:0.75in;background-color:rgba(233, 233, 233, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(190, 190, 190, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 1pt solid rgba(190, 190, 190, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-ccdc838c{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-ccdc8396{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-ccdc8397{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-ccdc8398{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1pt solid rgba(190, 190, 190, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-ccdc83a0{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1pt solid rgba(190, 190, 190, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-ccdc83a1{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1pt solid rgba(190, 190, 190, 1.00);border-top: 1pt solid rgba(190, 190, 190, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}fxTable examplegroup_levelresult_idcdm_namegroup_namevariable_namevariable_levelestimate_nameestimate_typeadditional_nameadditional_levelStudy strataoverallage_group &&& sexsexage_groupoverall<40 &&& Male>=40 &&& Male<40 &&& Female>=40 &&& FemaleMaleFemale<40>=40cohort11mockcohort_namenumber subjects--countintegeroveralloverall1,333,4859,272,8188,941,2272,036,6442,569,8296,140,0564,414,9923,155,9471,013,138age--meannumericoveralloverall26.241.643.918.27.81.872.897.153.5sdnumericoveralloverall9.64.59.85.43.65.00.79.76.5MedicationsAmoxicilinecountintegeroveralloverall45,67517,90396,62171,3412,48962,64682,79264,30770,848percentagepercentageoveralloverall0.86580747738480643.089879257604572.49350971542341.225638706237155.086239520460415.63605701085184.3001293204724868.46441130619551.4402497094125Ibuprofencountintegeroveralloverall34,97098,26740,88536,08765,25114,35668,08085,92983,863percentagepercentageoveralloverall11.304750083945797.026227973401564.80827818159015.607304326258647.313709580339529.462501313537461.029962194152212.110888026654762.9416507901624cohort21mockcohort_namenumber subjects--countintegeroveralloverall2,726,4626,536,9949,278,701266,2475,594,9128,541,737758,8302,058,2894,958,896age--meannumericoveralloverall16.65.845.962.359.574.352.449.71.5sdnumericoveralloverall9.85.47.65.67.86.43.83.68.4MedicationsAmoxicilinecountintegeroveralloverall87,07328,18117,32210,96758,62285,07292,15367,56635,059percentagepercentageoveralloverall94.56878483761184.3096942175186.4883093349635676.21109145693487.8384252265095713.350766268558880.969620100222555.938323936425173.3729686122388Ibuprofencountintegeroveralloverall88,13123,77057,86389,79034,44376,08673,11085,24397,582percentagepercentageoveralloverall71.195530286058861.20827866252513.4429233055561866.589078702963965.296727651730245.185843971557951.680410187691567.661079717888.0933094071224 # Example 2 mockSummarisedResult() |>   formatEstimateValue(decimals = c(integer = 0, numeric = 1)) |>   formatHeader(header = c(\"Study strata\", \"strata_name\", \"strata_level\"),               includeHeaderName = FALSE) |>   formatTable(     type = \"gt\",     style = list(\"header\" = list(       gt::cell_fill(color = \"#d9d9d9\"),       gt::cell_text(weight = \"bold\")),       \"header_level\" = list(gt::cell_fill(color = \"#e1e1e1\"),                             gt::cell_text(weight = \"bold\")),       \"column_name\" = list(gt::cell_text(weight = \"bold\")),       \"title\" = list(gt::cell_text(weight = \"bold\"),                      gt::cell_fill(color = \"#c8c8c8\")),       \"group_label\" = gt::cell_fill(color = \"#e1e1e1\")),     na = \"--\",     title = \"gtTable example\",     subtitle = NULL,     caption = NULL,     groupColumn = \"group_level\",     groupAsColumn = FALSE,     groupOrder = c(\"cohort1\", \"cohort2\"),     merge = \"all_columns\"   )     gtTable example                     Study strata            result_id       cdm_name       group_name       variable_name       variable_level       estimate_name       estimate_type       additional_name       additional_level                overall                       age_group &&& sex                       sex                       age_group            overall       <40 &&& Male       >=40 &&& Male       <40 &&& Female       >=40 &&& Female       Male       Female       <40       >=40     cohort1     1 mock cohort_name number subjects -- count integer overall overall 7,312,292 3,986,198 4,305,207 1,454,073 4,511,203 5,787,815 704,171 7,423,262 5,492,207   age -- mean numeric overall overall 77.8 65.8 25.9 91.8 14.9 64.1 20.1 74.4 84.8     sd numeric overall overall 4.4 9.0 7.7 1.3 5.4 1.3 5.1 5.4 2.4   Medications Amoxiciline count integer overall overall 36,924 12,667 73,987 95,587 66,867 46,809 53,819 33,095 62,868     percentage percentage overall overall 6.84064193628728 95.8503520581871 24.4483520975336 92.6283334614709 50.2747076796368 93.5517142061144 43.8799632480368 35.0486536743119 47.6504088379443    Ibuprofen count integer overall overall 13,002 79,191 35,590 96,434 11,868 45,816 52,365 83,706 3,350     percentage percentage overall overall 75.4406645428389 24.2454329272732 62.715786579065 16.8414602987468 44.4789632922038 16.4675234118477 11.8276783032343 36.7464390583336 94.6558905066922cohort2     1 mock cohort_name number subjects -- count integer overall overall 6,345,443 1,366,286 9,302,335 6,511,186 5,287,093 2,251,154 9,832,669 1,090,488 699,455   age -- mean numeric overall overall 85.4 80.3 2.4 79.5 88.7 60.0 43.3 92.0 61.6     sd numeric overall overall 8.0 9.5 4.1 5.1 9.8 3.5 4.6 2.2 0.8   Medications Amoxiciline count integer overall overall 45,255 88,802 78,420 13,806 28,131 70,695 44,219 67,770 70,071     percentage percentage overall overall 96.6159525094554 29.7161926981062 29.0648308349773 85.9722247580066 19.3312666844577 80.9108371380717 36.5486512426287 25.2699653152376 85.6081013800576    Ibuprofen count integer overall overall 4,333 79,210 20,270 6,880 86,444 7,709 43,100 97,362 57,096     percentage percentage overall overall 87.5410763313994 26.0058912448585 65.7298437319696 12.1864625485614 31.8848039023578 62.3061030171812 44.6997430175543 70.8293445874006 89.0028999885544"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/mockSummarisedResult.html","id":null,"dir":"Reference","previous_headings":"","what":"A <summarised_result> object filled with mock data — mockSummarisedResult","title":"A <summarised_result> object filled with mock data — mockSummarisedResult","text":"Creates object class <summarised_result> mock data illustration purposes.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/mockSummarisedResult.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"A <summarised_result> object filled with mock data — mockSummarisedResult","text":"","code":"mockSummarisedResult()"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/mockSummarisedResult.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"A <summarised_result> object filled with mock data — mockSummarisedResult","text":"object class <summarised_result> mock data.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/mockSummarisedResult.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"A <summarised_result> object filled with mock data — mockSummarisedResult","text":"","code":"mockSummarisedResult() #> # A tibble: 126 × 13 #>    result_id cdm_name group_name  group_level strata_name       strata_level    #>        <int> <chr>    <chr>       <chr>       <chr>             <chr>           #>  1         1 mock     cohort_name cohort1     overall           overall         #>  2         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Male    #>  3         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Male   #>  4         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Female  #>  5         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Female #>  6         1 mock     cohort_name cohort1     sex               Male            #>  7         1 mock     cohort_name cohort1     sex               Female          #>  8         1 mock     cohort_name cohort1     age_group         <40             #>  9         1 mock     cohort_name cohort1     age_group         >=40            #> 10         1 mock     cohort_name cohort2     overall           overall         #> # ℹ 116 more rows #> # ℹ 7 more variables: variable_name <chr>, variable_level <chr>, #> #   estimate_name <chr>, estimate_type <chr>, estimate_value <chr>, #> #   additional_name <chr>, additional_level <chr>"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/plotColumns.html","id":null,"dir":"Reference","previous_headings":"","what":"Columns for the plot functions — plotColumns","title":"Columns for the plot functions — plotColumns","text":"Names columns can used input arguments plot functions.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/plotColumns.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Columns for the plot functions — plotColumns","text":"","code":"plotColumns(result)"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/plotColumns.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Columns for the plot functions — plotColumns","text":"result <summarised_result> object.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/plotColumns.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Columns for the plot functions — plotColumns","text":"character vector supported columns plots.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/plotColumns.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Columns for the plot functions — plotColumns","text":"","code":"result <- mockSummarisedResult() plotColumns(result) #>  [1] \"cdm_name\"       \"cohort_name\"    \"age_group\"      \"sex\"            #>  [5] \"variable_name\"  \"variable_level\" \"count\"          \"mean\"           #>  [9] \"sd\"             \"percentage\""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/reexports.html","id":null,"dir":"Reference","previous_headings":"","what":"Objects exported from other packages — reexports","title":"Objects exported from other packages — reexports","text":"objects imported packages. Follow links see documentation. generics tidy omopgenerics additionalColumns, addSettings, bind, exportSummarisedResult, filterAdditional, filterGroup, filterSettings, filterStrata, groupColumns, importSummarisedResult, pivotEstimates, settings, settingsColumns, splitAdditional, splitAll, splitGroup, splitStrata, strataColumns, suppress, tidy, tidyColumns, uniteAdditional, uniteGroup, uniteStrata","code":""},{"path":[]},{"path":"https://darwin-eu.github.io/visOmopResults/reference/scatterPlot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a scatter plot visualisation from a <summarised_result> object — scatterPlot","text":"","code":"scatterPlot(   result,   x,   y,   line,   point,   ribbon,   ymin = NULL,   ymax = NULL,   facet = NULL,   colour = NULL,   group = colour,   label = character() )"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/scatterPlot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a scatter plot visualisation from a <summarised_result> object — scatterPlot","text":"result <summarised_result> object. x Column estimate name used x variable. y Column estimate name used y variable line Whether plot line using geom_line. point Whether plot points using geom_point. ribbon Whether plot ribbon using geom_ribbon. ymin Lower limit error bars, provided plot using geom_errorbar. ymax Upper limit error bars, provided plot using geom_errorbar. facet Variables facet , formula can provided specify variables used rows ones columns. colour Columns use determine colors. group Columns use determine group. label Character vector columns display interactively plotly.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/scatterPlot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a scatter plot visualisation from a <summarised_result> object — scatterPlot","text":"plot object.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/scatterPlot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a scatter plot visualisation from a <summarised_result> object — scatterPlot","text":"","code":"result <- mockSummarisedResult() |>   dplyr::filter(variable_name == \"age\")  scatterPlot(   result = result,   x = \"cohort_name\",   y = \"mean\",   line = TRUE,   point = TRUE,   ribbon = FALSE,   facet = age_group ~ sex) #> `geom_line()`: Each group consists of only one observation. #> ℹ Do you need to adjust the group aesthetic? #> `geom_line()`: Each group consists of only one observation. #> ℹ Do you need to adjust the group aesthetic? #> `geom_line()`: Each group consists of only one observation. #> ℹ Do you need to adjust the group aesthetic? #> `geom_line()`: Each group consists of only one observation. #> ℹ Do you need to adjust the group aesthetic? #> `geom_line()`: Each group consists of only one observation. #> ℹ Do you need to adjust the group aesthetic? #> `geom_line()`: Each group consists of only one observation. #> ℹ Do you need to adjust the group aesthetic? #> `geom_line()`: Each group consists of only one observation. #> ℹ Do you need to adjust the group aesthetic? #> `geom_line()`: Each group consists of only one observation. #> ℹ Do you need to adjust the group aesthetic? #> `geom_line()`: Each group consists of only one observation. #> ℹ Do you need to adjust the group aesthetic?"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableColumns.html","id":null,"dir":"Reference","previous_headings":"","what":"Columns for the table functions — tableColumns","title":"Columns for the table functions — tableColumns","text":"Names columns can used input arguments table functions.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableColumns.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Columns for the table functions — tableColumns","text":"","code":"tableColumns(result)"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableColumns.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Columns for the table functions — tableColumns","text":"result <summarised_result> object.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableColumns.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Columns for the table functions — tableColumns","text":"character vector supported columns tables.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableColumns.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Columns for the table functions — tableColumns","text":"","code":"result <- mockSummarisedResult() tableColumns(result) #> [1] \"cdm_name\"       \"cohort_name\"    \"age_group\"      \"sex\"            #> [5] \"variable_name\"  \"variable_level\" \"estimate_name\""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableOptions.html","id":null,"dir":"Reference","previous_headings":"","what":"Additional table formatting options for visOmopTable() and visTable() — tableOptions","title":"Additional table formatting options for visOmopTable() and visTable() — tableOptions","text":"function provides list allowed inputs .option argument visOmopTable() visTable(), corresponding default values.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableOptions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Additional table formatting options for visOmopTable() and visTable() — tableOptions","text":"","code":"tableOptions()"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableOptions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Additional table formatting options for visOmopTable() and visTable() — tableOptions","text":"named list default options table customization.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableOptions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Additional table formatting options for visOmopTable() and visTable() — tableOptions","text":"","code":"tableOptions() #> $decimals #>    integer percentage    numeric proportion  #>          0          2          2          2  #>  #> $decimalMark #> [1] \".\" #>  #> $bigMark #> [1] \",\" #>  #> $keepNotFormatted #> [1] TRUE #>  #> $useFormatOrder #> [1] TRUE #>  #> $delim #> [1] \"\\n\" #>  #> $includeHeaderName #> [1] TRUE #>  #> $includeHeaderKey #> [1] TRUE #>  #> $style #> [1] \"default\" #>  #> $na #> [1] \"-\" #>  #> $title #> NULL #>  #> $subtitle #> NULL #>  #> $caption #> NULL #>  #> $groupAsColumn #> [1] FALSE #>  #> $groupOrder #> NULL #>  #> $merge #> [1] \"all_columns\" #>"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableStyle.html","id":null,"dir":"Reference","previous_headings":"","what":"Supported predefined styles for formatted tables — tableStyle","title":"Supported predefined styles for formatted tables — tableStyle","text":"Supported predefined styles formatted tables","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableStyle.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Supported predefined styles for formatted tables — tableStyle","text":"","code":"tableStyle(type = \"gt\", styleName = \"default\")"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableStyle.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Supported predefined styles for formatted tables — tableStyle","text":"type Character string specifying formatted table class. See tableType() supported classes. Default \"gt\". styleName character string specifying style name. Currently, package supports one predefined style: \"default\".","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableStyle.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Supported predefined styles for formatted tables — tableStyle","text":"code expression selected style table type.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableStyle.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Supported predefined styles for formatted tables — tableStyle","text":"","code":"tableStyle(\"gt\") #> list(header = list(gt::cell_fill(color = \"#c8c8c8\"), gt::cell_text(weight = \"bold\",  #>     align = \"center\")), header_name = list(gt::cell_fill(color = \"#d9d9d9\"),  #>     gt::cell_text(weight = \"bold\", align = \"center\")), header_level = list(gt::cell_fill(color = \"#e1e1e1\"),  #>     gt::cell_text(weight = \"bold\", align = \"center\")), column_name = list(gt::cell_text(weight = \"bold\",  #>     align = \"center\")), group_label = list(gt::cell_fill(color = \"#e9e9e9\"),  #>     gt::cell_text(weight = \"bold\")), title = list(gt::cell_text(weight = \"bold\",  #>     size = 15, align = \"center\")), subtitle = list(gt::cell_text(weight = \"bold\",  #>     size = 12, align = \"center\")), body = list()) tableStyle(\"flextable\") #> list(header = list(cell = officer::fp_cell(background.color = \"#c8c8c8\"),  #>     text = officer::fp_text(bold = TRUE)), header_name = list(cell = officer::fp_cell(background.color = \"#d9d9d9\"),  #>     text = officer::fp_text(bold = TRUE)), header_level = list(cell = officer::fp_cell(background.color = \"#e1e1e1\"),  #>     text = officer::fp_text(bold = TRUE)), column_name = list(text = officer::fp_text(bold = TRUE)),  #>     group_label = list(cell = officer::fp_cell(background.color = \"#e9e9e9\",  #>         border = officer::fp_border(color = \"gray\")), text = officer::fp_text(bold = TRUE)),  #>     title = list(text = officer::fp_text(bold = TRUE, font.size = 15)),  #>     subtitle = list(text = officer::fp_text(bold = TRUE, font.size = 12)),  #>     body = list())"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableType.html","id":null,"dir":"Reference","previous_headings":"","what":"Supported table classes — tableType","title":"Supported table classes — tableType","text":"function returns supported table classes can used type argument visOmopTable(), visTable(), formatTable() functions.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableType.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Supported table classes — tableType","text":"","code":"tableType()"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableType.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Supported table classes — tableType","text":"character vector supported table types.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableType.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Supported table classes — tableType","text":"","code":"tableType() #> [1] \"gt\"        \"flextable\" \"tibble\"    \"datatable\""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/themeVisOmop.html","id":null,"dir":"Reference","previous_headings":"","what":"Apply visOmopResults default styling to a ggplot — themeVisOmop","title":"Apply visOmopResults default styling to a ggplot — themeVisOmop","text":"Apply visOmopResults default styling ggplot","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/themeVisOmop.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Apply visOmopResults default styling to a ggplot — themeVisOmop","text":"","code":"themeVisOmop(fontsizeRef = 13, legendPosition = \"right\")"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/themeVisOmop.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Apply visOmopResults default styling to a ggplot — themeVisOmop","text":"fontsizeRef integer use reference adjusting label fontsize. legendPosition legend, go? Options ggplot. default right side.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/themeVisOmop.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Apply visOmopResults default styling to a ggplot — themeVisOmop","text":"","code":"result <- mockSummarisedResult() |> dplyr::filter(variable_name == \"age\")  barPlot(   result = result,   x = \"cohort_name\",   y = \"mean\",   facet = c(\"age_group\", \"sex\"),   colour = \"sex\") +   themeVisOmop()"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visOmopResults-package.html","id":null,"dir":"Reference","previous_headings":"","what":"visOmopResults: Graphs and Tables for OMOP Results — visOmopResults-package","title":"visOmopResults: Graphs and Tables for OMOP Results — visOmopResults-package","text":"Provides methods transform omop_result objects formatted tables figures, facilitating visualization study results working Observational Medical Outcomes Partnership (OMOP) Common Data Model.","code":""},{"path":[]},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visOmopResults-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"visOmopResults: Graphs and Tables for OMOP Results — visOmopResults-package","text":"Maintainer: Núria Mercadé-Besora nuria.mercadebesora@ndorms.ox.ac.uk (ORCID) Authors: Martí Català marti.catalasabate@ndorms.ox.ac.uk (ORCID) contributors: Yuchen Guo yuchen.guo@ndorms.ox.ac.uk (ORCID) [contributor] Elin Rowlands elin.rowlands@ndorms.ox.ac.uk (ORCID) [contributor] Edward Burn edward.burn@ndorms.ox.ac.uk (ORCID) [contributor]","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visOmopTable.html","id":null,"dir":"Reference","previous_headings":"","what":"Format a <summarised_result> object into a gt, flextable, or tibble object — visOmopTable","title":"Format a <summarised_result> object into a gt, flextable, or tibble object — visOmopTable","text":"function combines functionalities formatEstimateValue(), estimateName(), formatHeader(), formatTable() single function specifically <summarised_result> objects.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visOmopTable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format a <summarised_result> object into a gt, flextable, or tibble object — visOmopTable","text":"","code":"visOmopTable(   result,   estimateName = character(),   header = character(),   settingsColumn = character(),   groupColumn = character(),   rename = character(),   type = \"gt\",   hide = character(),   columnOrder = character(),   factor = list(),   showMinCellCount = TRUE,   .options = list(),   settingsColumns = lifecycle::deprecated() )"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visOmopTable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format a <summarised_result> object into a gt, flextable, or tibble object — visOmopTable","text":"result <summarised_result> object. estimateName named list estimate names join, sorted computation order. Use <...> indicate estimate names. header vector specifying elements include header. order elements matters, first topmost header. Elements header can : columns returned tableColumns(result) create header columns. input create overall header. settingsColumn character vector names settings include table. see options use settingsColumns(result). groupColumn Columns use group labels, see options use tableColumns(result). default, name new group tidy* column names separated \";\". specify custom group name, use named list : list(\"newGroupName\" = c(\"variable_name\", \"variable_level\")). *tidy: tidy format applied column names replaces \"_\" space converts sentence case. Use rename customize specific column names. rename named vector customize column names, e.g., c(\"Database name\" = \"cdm_name\"). function renames column names specified tidy* format. type desired format output table. See tableType() allowed options. hide Columns drop output table. default, result_id estimate_type always dropped. columnOrder Character vector establishing position columns formatted table. Columns either header, groupColumn, hide ignored. factor named list names refer columns (see available columns tableColumns()) list elements level order column arrange results. column order list used arranging result. showMinCellCount TRUE, suppressed estimates indicated \"<{min_cell_count}\", otherwise, default na defined .options used. .options named list additional formatting options. visOmopResults::tableOptions() shows allowed arguments default values. settingsColumns","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visOmopTable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format a <summarised_result> object into a gt, flextable, or tibble object — visOmopTable","text":"tibble, gt, flextable object.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visOmopTable.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format a <summarised_result> object into a gt, flextable, or tibble object — visOmopTable","text":"","code":"result <- mockSummarisedResult() result |>   visOmopTable(     estimateName = c(\"N%\" = \"<count> (<percentage>)\",                      \"N\" = \"<count>\",                      \"Mean (SD)\" = \"<mean> (<sd>)\"),     header = c(\"group\"),     rename = c(\"Database name\" = \"cdm_name\"),     groupColumn = strataColumns(result)   )     Database name       Variable name       Variable level       Estimate name                Cohort name            cohort1       cohort2     overall; overall     mock number subjects - N 2,009,283 3,012,543 age - Mean (SD) 27.92 (5.88) 33.71 (6.72) Medications Amoxiciline N% 82,683 (49.14) 20,832 (29.82)  Ibuprofen N% 90,252 (24.88) 54,539 (58.02)<40; Male     mock number subjects - N 8,141,156 7,204,667 age - Mean (SD) 67.27 (4.92) 14.12 (8.20) Medications Amoxiciline N% 61,938 (84.54) 22,826 (38.13)  Ibuprofen N% 43,803 (74.80) 72,510 (38.57)>=40; Male     mock number subjects - N 6,537,801 2,614,054 age - Mean (SD) 6.01 (2.86) 35.26 (9.15) Medications Amoxiciline N% 84,105 (2.51) 5,044 (24.78)  Ibuprofen N% 80,676 (40.72) 52,548 (23.65)<40; Female     mock number subjects - N 3,532,520 1,076,963 age - Mean (SD) 98.85 (0.08) 40.14 (6.90) Medications Amoxiciline N% 42,725 (54.84) 56,182 (34.50)  Ibuprofen N% 48,150 (56.17) 61,894 (51.95)>=40; Female     mock number subjects - N 5,965,949 2,624,227 age - Mean (SD) 28.23 (5.51) 88.89 (4.92) Medications Amoxiciline N% 76,929 (95.55) 69,425 (41.98)  Ibuprofen N% 25,804 (75.05) 17,896 (64.12)overall; Male     mock number subjects - N 7,277,044 1,867,062 age - Mean (SD) 55.41 (8.13) 31.26 (6.47) Medications Amoxiciline N% 71,214 (14.05) 22,794 (65.91)  Ibuprofen N% 17,014 (55.12) 76,772 (82.99)overall; Female     mock number subjects - N 9,955,685 5,424,417 age - Mean (SD) 89.01 (6.44) 6.17 (4.57) Medications Amoxiciline N% 6,337 (71.03) 96,031 (95.40)  Ibuprofen N% 16,061 (47.33) 81,629 (91.91)<40; overall     mock number subjects - N 4,980,553 655,185 age - Mean (SD) 2.28 (0.69) 67.95 (1.25) Medications Amoxiciline N% 42,601 (12.64) 49,284 (46.99)  Ibuprofen N% 66,139 (6.26) 19,458 (92.94)>=40; overall     mock number subjects - N 2,302,948 8,803,851 age - Mean (SD) 67.77 (7.29) 37.82 (6.04) Medications Amoxiciline N% 8,828 (83.57) 72,321 (15.06)  Ibuprofen N% 46,855 (9.39) 21,251 (64.53)"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visTable.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate a formatted table from a <data.table> — visTable","title":"Generate a formatted table from a <data.table> — visTable","text":"function combines functionalities formatEstimateValue(), formatEstimateName(), formatHeader(), formatTable() single function. require input table <summarised_result>, expect specific fields apply formatting functionalities.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visTable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate a formatted table from a <data.table> — visTable","text":"","code":"visTable(   result,   estimateName = character(),   header = character(),   groupColumn = character(),   rename = character(),   type = \"gt\",   hide = character(),   .options = list() )"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visTable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate a formatted table from a <data.table> — visTable","text":"result table format. estimateName named list estimate names join, sorted computation order. Use <...> indicate estimate names. argument requires table estimate_name estimate_value columns. header vector specifying elements include header. order elements matters, first topmost header. vector elements can column names labels overall headers. table must contain estimate_value column pivot headers. groupColumn Columns use group labels. default, name new group tidy* column names separated \";\". specify custom group name, use named list : list(\"newGroupName\" = c(\"variable_name\", \"variable_level\")). *tidy: tidy format applied column names replaces \"_\" space converts sentence case. Use rename customize specific column names. rename named vector customize column names, e.g., c(\"Database name\" = \"cdm_name\"). function rename column names specified tidy* format. type desired format output table. See tableType() allowed options. hide Columns drop output table. .options named list additional formatting options. visOmopResults::tableOptions() shows allowed arguments default values.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visTable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate a formatted table from a <data.table> — visTable","text":"tibble, gt, flextable object.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visTable.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate a formatted table from a <data.table> — visTable","text":"","code":"result <- mockSummarisedResult() result |>   visTable(     estimateName = c(\"N%\" = \"<count> (<percentage>)\",                      \"N\" = \"<count>\",                      \"Mean (SD)\" = \"<mean> (<sd>)\"),     header = c(\"Estimate\"),     rename = c(\"Database name\" = \"cdm_name\"),     groupColumn = c(\"strata_name\", \"strata_level\"),     hide = c(\"additional_name\", \"additional_level\", \"estimate_type\", \"result_type\")   )     Result id       Database name       Group name       Group level       Variable name       Variable level       Estimate name       Estimate     overall; overall     1 mock cohort_name cohort1 number subjects - N 2,202,471   cohort2 number subjects - N 4,513,757   cohort1 age - Mean (SD) 44.81 (7.83)   cohort2 age - Mean (SD) 26.89 (7.36)   cohort1 Medications Amoxiciline N% 62,237 (92.84)   cohort2 Medications Amoxiciline N% 33,863 (63.98)   cohort1 Medications Ibuprofen N% 24,332 (61.44)   cohort2 Medications Ibuprofen N% 16,482 (1.81)age_group &&& sex; <40 &&& Male     1 mock cohort_name cohort1 number subjects - N 371,822   cohort2 number subjects - N 7,942,700   cohort1 age - Mean (SD) 82.39 (6.22)   cohort2 age - Mean (SD) 88.35 (9.41)   cohort1 Medications Amoxiciline N% 55,533 (41.34)   cohort2 Medications Amoxiciline N% 76,968 (88.25)   cohort1 Medications Ibuprofen N% 51,505 (19.24)   cohort2 Medications Ibuprofen N% 18,098 (38.20)age_group &&& sex; >=40 &&& Male     1 mock cohort_name cohort1 number subjects - N 6,980,541   cohort2 number subjects - N 8,246,223   cohort1 age - Mean (SD) 96.94 (8.66)   cohort2 age - Mean (SD) 67.06 (8.61)   cohort1 Medications Amoxiciline N% 96,107 (13.10)   cohort2 Medications Amoxiciline N% 30,134 (94.62)   cohort1 Medications Ibuprofen N% 86,319 (7.18)   cohort2 Medications Ibuprofen N% 99,645 (51.36)age_group &&& sex; <40 &&& Female     1 mock cohort_name cohort1 number subjects - N 1,498,340   cohort2 number subjects - N 2,090,516   cohort1 age - Mean (SD) 29.54 (9.20)   cohort2 age - Mean (SD) 7.43 (3.64)   cohort1 Medications Amoxiciline N% 91,564 (6.12)   cohort2 Medications Amoxiciline N% 62,964 (70.94)   cohort1 Medications Ibuprofen N% 4,056 (30.62)   cohort2 Medications Ibuprofen N% 64,511 (4.72)age_group &&& sex; >=40 &&& Female     1 mock cohort_name cohort1 number subjects - N 5,424,376   cohort2 number subjects - N 1,682,065   cohort1 age - Mean (SD) 23.27 (3.25)   cohort2 age - Mean (SD) 68.53 (9.13)   cohort1 Medications Amoxiciline N% 60,328 (88.61)   cohort2 Medications Amoxiciline N% 80,250 (92.36)   cohort1 Medications Ibuprofen N% 46,003 (17.46)   cohort2 Medications Ibuprofen N% 91,810 (80.31)sex; Male     1 mock cohort_name cohort1 number subjects - N 7,967,724   cohort2 number subjects - N 9,802,742   cohort1 age - Mean (SD) 32.55 (9.16)   cohort2 age - Mean (SD) 60.08 (7.53)   cohort1 Medications Amoxiciline N% 31,155 (59.22)   cohort2 Medications Amoxiciline N% 54,224 (1.62)   cohort1 Medications Ibuprofen N% 16,600 (88.78)   cohort2 Medications Ibuprofen N% 79,507 (63.41)sex; Female     1 mock cohort_name cohort1 number subjects - N 7,196,247   cohort2 number subjects - N 6,006,700   cohort1 age - Mean (SD) 10.04 (0.81)   cohort2 age - Mean (SD) 70.61 (6.41)   cohort1 Medications Amoxiciline N% 55,515 (72.24)   cohort2 Medications Amoxiciline N% 63,100 (17.15)   cohort1 Medications Ibuprofen N% 91,538 (49.78)   cohort2 Medications Ibuprofen N% 91,310 (77.13)age_group; <40     1 mock cohort_name cohort1 number subjects - N 7,281,897   cohort2 number subjects - N 1,516,763   cohort1 age - Mean (SD) 33.02 (8.56)   cohort2 age - Mean (SD) 46.82 (7.95)   cohort1 Medications Amoxiciline N% 93,760 (51.24)   cohort2 Medications Amoxiciline N% 18,979 (21.40)   cohort1 Medications Ibuprofen N% 40,942 (69.39)   cohort2 Medications Ibuprofen N% 39,056 (50.18)age_group; >=40     1 mock cohort_name cohort1 number subjects - N 478,162   cohort2 number subjects - N 2,927,387   cohort1 age - Mean (SD) 19.26 (3.05)   cohort2 age - Mean (SD) 1.10 (9.85)   cohort1 Medications Amoxiciline N% 36,504 (29.61)   cohort2 Medications Amoxiciline N% 20,345 (84.51)   cohort1 Medications Ibuprofen N% 64,053 (87.42)   cohort2 Medications Ibuprofen N% 35,740 (71.13)"}]
+[{"path":"https://darwin-eu.github.io/visOmopResults/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"Apache License","title":"Apache License","text":"Version 2.0, January 2004 <http://www.apache.org/licenses/>","code":""},{"path":[]},{"path":"https://darwin-eu.github.io/visOmopResults/LICENSE.html","id":"id_1-definitions","dir":"","previous_headings":"Terms and Conditions for use, reproduction, and distribution","what":"1. Definitions","title":"Apache License","text":"“License” shall mean terms conditions use, reproduction, distribution defined Sections 1 9 document. “Licensor” shall mean copyright owner entity authorized copyright owner granting License. “Legal Entity” shall mean union acting entity entities control, controlled , common control entity. purposes definition, “control” means () power, direct indirect, cause direction management entity, whether contract otherwise, (ii) ownership fifty percent (50%) outstanding shares, (iii) beneficial ownership entity. “” (“”) shall mean individual Legal Entity exercising permissions granted License. “Source” form shall mean preferred form making modifications, including limited software source code, documentation source, configuration files. “Object” form shall mean form resulting mechanical transformation translation Source form, including limited compiled object code, generated documentation, conversions media types. “Work” shall mean work authorship, whether Source Object form, made available License, indicated copyright notice included attached work (example provided Appendix ). “Derivative Works” shall mean work, whether Source Object form, based (derived ) Work editorial revisions, annotations, elaborations, modifications represent, whole, original work authorship. purposes License, Derivative Works shall include works remain separable , merely link (bind name) interfaces , Work Derivative Works thereof. “Contribution” shall mean work authorship, including original version Work modifications additions Work Derivative Works thereof, intentionally submitted Licensor inclusion Work copyright owner individual Legal Entity authorized submit behalf copyright owner. purposes definition, “submitted” means form electronic, verbal, written communication sent Licensor representatives, including limited communication electronic mailing lists, source code control systems, issue tracking systems managed , behalf , Licensor purpose discussing improving Work, excluding communication conspicuously marked otherwise designated writing copyright owner “Contribution.” “Contributor” shall mean Licensor individual Legal Entity behalf Contribution received Licensor subsequently incorporated within Work.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/LICENSE.html","id":"id_2-grant-of-copyright-license","dir":"","previous_headings":"Terms and Conditions for use, reproduction, and distribution","what":"2. 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Accepting Warranty or Additional Liability","title":"Apache License","text":"redistributing Work Derivative Works thereof, may choose offer, charge fee , acceptance support, warranty, indemnity, liability obligations /rights consistent License. However, accepting obligations, may act behalf sole responsibility, behalf Contributor, agree indemnify, defend, hold Contributor harmless liability incurred , claims asserted , Contributor reason accepting warranty additional liability. END TERMS CONDITIONS","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/LICENSE.html","id":"appendix-how-to-apply-the-apache-license-to-your-work","dir":"","previous_headings":"","what":"APPENDIX: How to apply the Apache License to your work","title":"Apache License","text":"apply Apache License work, attach following boilerplate notice, fields enclosed brackets [] replaced identifying information. (Don’t include brackets!) text enclosed appropriate comment syntax file format. also recommend file class name description purpose included “printed page” copyright notice easier identification within third-party archives.","code":"Copyright [yyyy] [name of copyright owner]  Licensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at    http://www.apache.org/licenses/LICENSE-2.0  Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License."},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a01_tables.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"Tables","text":"visOmopResults package provides user-friendly tools creating well-formatted tables plots publication-ready. vignette, focus specifically table formatting functionalities. package supports four table formats: <tibble>, <gt>, <flextable>, <datatables>. <tibble> <data.frame> R object, <gt> <flextable> designed create publication-ready tables can exported different formats (e.g., PNG, Word, PDF, HTML), <datatables> display tables HTML pages. last three can used ShinyApps, RMarkdown, Quarto, . Although primary aim package simplify handling <summarised_result> class (see omopgenerics details), functionalities can applied <data.frame> certain requirements met.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a01_tables.html","id":"types-of-table-functions","dir":"Articles","previous_headings":"Introduction","what":"Types of Table Functions","title":"Tables","text":"two main categories table functions package: Main Table Functions: Comprehensive functions like visOmopTable() visTable() allow users fully format tables, including specifying headers, grouping columns, customising styles. Additional Table Formatting Functions: format function set provides granular control specific table elements, enabling advanced customisation beyond main functions. vignette guide usage functions.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a01_tables.html","id":"main-functions","dir":"Articles","previous_headings":"","what":"Main Functions","title":"Tables","text":"functions built top format functions, providing quick straightforward way format tables.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a01_tables.html","id":"vistable","dir":"Articles","previous_headings":"Main Functions","what":"visTable()","title":"Tables","text":"visTable() flexible function designed format <data.frame>. Let’s demonstrate usage dataset palmerpenguins package. can format data <gt> table using visTable() follows: use arguments estimateName header, <data.frame> must estimates arranged three columns: estimate_name, estimate_type, estimate_value. Let’s reshape example dataset accordingly demonstrate creating <flextable> object: Sex Estimate name Species Adelie Gentoo Chinstrap Island Biscoe Torgersen Dream Biscoe Dream female   Bill length - Bill depth (mm) 36.64 - 17.22 36.61 - 17.40 36.27 - 17.79 45.30 - 14.13 46.00 - 17.30  Flipper length (mm) 186.56 190.00 189.00 213.00 192.67 male   Bill length - Bill depth (mm) 40.76 - 19.03 40.92 - 18.84 40.11 - 18.89 48.54 - 15.70 51.40 - 19.60  Flipper length (mm) 192.56 193.50 195.00 222.09 202.78","code":"library(visOmopResults) library(palmerpenguins) library(dplyr) library(tidyr) x <- penguins |>    filter(!is.na(sex) & year == 2008) |>    select(!\"body_mass_g\") |>   summarise(across(ends_with(\"mm\"), ~mean(.x)), .by = c(\"species\", \"island\", \"sex\")) head(x) #> # A tibble: 6 × 6 #>   species island    sex    bill_length_mm bill_depth_mm flipper_length_mm #>   <fct>   <fct>     <fct>           <dbl>         <dbl>             <dbl> #> 1 Adelie  Biscoe    female           36.6          17.2              187. #> 2 Adelie  Biscoe    male             40.8          19.0              193. #> 3 Adelie  Torgersen female           36.6          17.4              190  #> 4 Adelie  Torgersen male             40.9          18.8              194. #> 5 Adelie  Dream     female           36.3          17.8              189  #> 6 Adelie  Dream     male             40.1          18.9              195 visTable(   result = x,   groupColumn = c(\"sex\"),   rename = c(\"Bill length (mm)\" = \"bill_length_mm\",              \"Bill depth (mm)\" = \"bill_depth_mm\",              \"Flipper length (mm)\" = \"flipper_length_mm\",              \"Body mass (g)\" = \"body_mass_g\"),   type = \"gt\",   hide = \"year\" ) # Transforming the dataset to include estimate columns x <- x |>   pivot_longer(     cols = ends_with(\"_mm\"),      names_to = \"estimate_name\",      values_to = \"estimate_value\"   ) |>   mutate(estimate_type = \"numeric\")  # Creating a formatted flextable visTable(   result = x,   estimateName = c(     \"Bill length - Bill depth (mm)\" = \"<bill_length_mm> - <bill_depth_mm>\",     \"Flipper length (mm)\" = \"<flipper_length_mm>\"   ),   header = c(\"species\", \"island\"),   groupColumn = \"sex\",   type = \"flextable\",   hide = c(\"year\", \"estimate_type\") )"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a01_tables.html","id":"visomoptable","dir":"Articles","previous_headings":"Main Functions","what":"visOmopTable()","title":"Tables","text":"visOmopTable() extends functionality visTable() additional features tailored specifically handling <summarised_result> objects, making easier work standardized result formats. Let’s demonstrate visOmopTable() mock <summarised_result>: workflow quite similar visTable(), includes specific enhancements <summarised_result> objects: Automatic splitting: result object always processed using splitAll() function. Thereby, column names use arguments must based split result. settingsColumn argument: Use argument specify settings displayed main table. columns specified can also referenced arguments header, rename, groupColumn. header argument: accepts specific <summarised_result> inputs, addition typical usage visTable(). example, use “strata” header display variables strata_name, use “settings” show settings specified settingsColumns. Hidden columns: result_id estimate_type columns always hidden serve helper columns internal processes. Suppressed estimates: result object processed suppress(), obscured estimates can displayed default na value “<{minCellCount}” corresponding minimum count value used. can controlled using showMinCellCount argument. next example, visOmopTable() generates <gt> table displaying suppressed estimates (counts 1,000,000) specified minimum cell count.","code":"# Creating a mock summarised result result <- mockSummarisedResult() |>   filter(strata_name == \"age_group &&& sex\")  # Displaying the first few rows head(result) #> # A tibble: 6 × 13 #>   result_id cdm_name group_name  group_level strata_name       strata_level    #>       <int> <chr>    <chr>       <chr>       <chr>             <chr>           #> 1         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Male    #> 2         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Male   #> 3         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Female  #> 4         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Female #> 5         1 mock     cohort_name cohort2     age_group &&& sex <40 &&& Male    #> 6         1 mock     cohort_name cohort2     age_group &&& sex >=40 &&& Male   #> # ℹ 7 more variables: variable_name <chr>, variable_level <chr>, #> #   estimate_name <chr>, estimate_type <chr>, estimate_value <chr>, #> #   additional_name <chr>, additional_level <chr>  # Creating a formatted gt table visOmopTable(   result = result,   estimateName = c(     \"N%\" = \"<count> (<percentage>)\",     \"N\" = \"<count>\",     \"Mean (SD)\" = \"<mean> (<sd>)\"   ),   header = c(\"package_name\", \"age_group\"),   groupColumn = c(\"cohort_name\", \"sex\"),   settingsColumn = \"package_name\",   type = \"gt\" ) result |>   suppress(minCellCount = 1000000) |>   visOmopTable(     estimateName = c(       \"N%\" = \"<count> (<percentage>)\",       \"N\" = \"<count>\",       \"Mean (SD)\" = \"<mean> (<sd>)\"     ),     header = c(\"My visOmopTable\", \"group\"),     groupColumn = c(\"strata\"),     hide = c(\"cdm_name\"),     showMinCellCount = TRUE,     type = \"gt\"   )"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a01_tables.html","id":"styling-tables","dir":"Articles","previous_headings":"Main Functions","what":"Styling tables","title":"Tables","text":"Tables displayed visOmopResults() follow default style, customisation possible .options argument. argument allows users modify various formatting aspects using options format functions (see format Functions section learn ). table details format function styling option belongs , along description option: view default .options settings used vis tables, use following function:","code":"tableOptions() #> $decimals #>    integer percentage    numeric proportion  #>          0          2          2          2  #>  #> $decimalMark #> [1] \".\" #>  #> $bigMark #> [1] \",\" #>  #> $keepNotFormatted #> [1] TRUE #>  #> $useFormatOrder #> [1] TRUE #>  #> $delim #> [1] \"\\n\" #>  #> $includeHeaderName #> [1] TRUE #>  #> $includeHeaderKey #> [1] TRUE #>  #> $style #> [1] \"default\" #>  #> $na #> [1] \"-\" #>  #> $title #> NULL #>  #> $subtitle #> NULL #>  #> $caption #> NULL #>  #> $groupAsColumn #> [1] FALSE #>  #> $groupOrder #> NULL #>  #> $merge #> [1] \"all_columns\""},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a01_tables.html","id":"styling-tables-1","dir":"Articles","previous_headings":"Main Functions > Styling tables","what":"Styling tables","title":"Tables","text":"inspect code default styles different table types supported, can use following function:","code":"tableStyle(type = \"gt\") #> list(header = list(gt::cell_fill(color = \"#c8c8c8\"), gt::cell_text(weight = \"bold\",  #>     align = \"center\")), header_name = list(gt::cell_fill(color = \"#d9d9d9\"),  #>     gt::cell_text(weight = \"bold\", align = \"center\")), header_level = list(gt::cell_fill(color = \"#e1e1e1\"),  #>     gt::cell_text(weight = \"bold\", align = \"center\")), column_name = list(gt::cell_text(weight = \"bold\",  #>     align = \"center\")), group_label = list(gt::cell_fill(color = \"#e9e9e9\"),  #>     gt::cell_text(weight = \"bold\")), title = list(gt::cell_text(weight = \"bold\",  #>     size = 15, align = \"center\")), subtitle = list(gt::cell_text(weight = \"bold\",  #>     size = 12, align = \"center\")), body = list())  tableStyle(type = \"flextable\") #> list(header = list(cell = officer::fp_cell(background.color = \"#c8c8c8\"),  #>     text = officer::fp_text(bold = TRUE)), header_name = list(cell = officer::fp_cell(background.color = \"#d9d9d9\"),  #>     text = officer::fp_text(bold = TRUE)), header_level = list(cell = officer::fp_cell(background.color = \"#e1e1e1\"),  #>     text = officer::fp_text(bold = TRUE)), column_name = list(text = officer::fp_text(bold = TRUE)),  #>     group_label = list(cell = officer::fp_cell(background.color = \"#e9e9e9\",  #>         border = officer::fp_border(color = \"gray\")), text = officer::fp_text(bold = TRUE)),  #>     title = list(text = officer::fp_text(bold = TRUE, font.size = 15)),  #>     subtitle = list(text = officer::fp_text(bold = TRUE, font.size = 12)),  #>     body = list())  tableStyle(type = \"datatable\") #> list(caption = \"caption-side: bottom; text-align: center;\", scrollX = TRUE,  #>     scrollY = 400, scroller = TRUE, deferRender = TRUE, scrollCollapse = TRUE,  #>     fixedColumns = list(leftColumns = 1, rightColumns = 1), fixedHeader = TRUE,  #>     pageLength = 10, lengthMenu = c(5, 10, 20, 50, 100), filter = \"bottom\",  #>     searchHighlight = TRUE, rownames = FALSE)"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a01_tables.html","id":"format-functions","dir":"Articles","previous_headings":"","what":"format Functions","title":"Tables","text":"format set functions can used pipeline transform format <data.frame> <summarised_result> object. , ’ll demonstrate utilize functions step--step manner.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a01_tables.html","id":"format-estimates","dir":"Articles","previous_headings":"format Functions","what":"1) Format Estimates","title":"Tables","text":"formatEstimateName() formatEstimateValue() functions enable customise naming display estimates table. illustrate usage, ’ll continue result dataset. Let’s first take look estimates formatting applied:","code":"result |>    filterGroup(cohort_name == \"cohort1\") |>  # visOmopResult filter function   filterStrata(age_group == \"<40\", sex == \"Female\") |>  # visOmopResult filter function   select(variable_name, variable_level, estimate_name, estimate_type, estimate_value) #> # A tibble: 7 × 5 #>   variable_name   variable_level estimate_name estimate_type estimate_value   #>   <chr>           <chr>          <chr>         <chr>         <chr>            #> 1 number subjects NA             count         integer       1956698          #> 2 age             NA             mean          numeric       63.6465614894405 #> 3 age             NA             sd            numeric       3.15241752425209 #> 4 Medications     Amoxiciline    count         integer       27860            #> 5 Medications     Amoxiciline    percentage    percentage    21.3172711199149 #> 6 Medications     Ibuprofen      count         integer       66887            #> 7 Medications     Ibuprofen      percentage    percentage    91.8803214561194"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a01_tables.html","id":"estimate-values","dir":"Articles","previous_headings":"format Functions > 1) Format Estimates","what":"1.1) Estimate values","title":"Tables","text":"formatEstimateValue() function allows specify number decimals different estimate_types estimate_names, well customise decimal thousand separators. Let’s see previous estimates updated afterwars: can see, estimates now reflect specified formatting rules.","code":"# Formatting estimate values result <- result |>   formatEstimateValue(     decimals = c(integer = 0, numeric = 4, percentage = 2),     decimalMark = \".\",     bigMark = \",\"   )  # Displaying the formatted subset result |>    filterGroup(cohort_name == \"cohort1\") |>     filterStrata(age_group == \"<40\", sex == \"Female\") |>    select(variable_name, variable_level, estimate_name, estimate_type, estimate_value) #> # A tibble: 7 × 5 #>   variable_name   variable_level estimate_name estimate_type estimate_value #>   <chr>           <chr>          <chr>         <chr>         <chr>          #> 1 number subjects NA             count         integer       1,956,698      #> 2 age             NA             mean          numeric       63.6466        #> 3 age             NA             sd            numeric       3.1524         #> 4 Medications     Amoxiciline    count         integer       27,860         #> 5 Medications     Amoxiciline    percentage    percentage    21.32          #> 6 Medications     Ibuprofen      count         integer       66,887         #> 7 Medications     Ibuprofen      percentage    percentage    91.88"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a01_tables.html","id":"estimate-names","dir":"Articles","previous_headings":"format Functions > 1) Format Estimates","what":"1.2) Estimate names","title":"Tables","text":"Next, format estimate names using formatEstimateName() function. function allows us combine counts percentages “N (%)”, among estimate combinations Now, estimate names displayed specified, “N (%)” counts percentages. keepNotFormatted argument ensures unformatted rows remain dataset, useFormatOrder allows control display order estimates.","code":"# Formatting estimate names result <- result |>    formatEstimateName(     estimateName = c(       \"N (%)\" = \"<count> (<percentage>%)\",        \"N\" = \"<count>\",       \"Mean (SD)\" = \"<mean> (<sd>)\"     ),     keepNotFormatted = TRUE,     useFormatOrder = FALSE   )  # Displaying the formatted subset with new estimate names result |>    filterGroup(cohort_name == \"cohort1\") |>     filterStrata(age_group == \"<40\", sex == \"Female\") |>    select(variable_name, variable_level, estimate_name, estimate_type, estimate_value) #> # A tibble: 4 × 5 #>   variable_name   variable_level estimate_name estimate_type estimate_value   #>   <chr>           <chr>          <chr>         <chr>         <chr>            #> 1 number subjects NA             N             character     1,956,698        #> 2 age             NA             Mean (SD)     character     63.6466 (3.1524) #> 3 Medications     Amoxiciline    N (%)         character     27,860 (21.32%)  #> 4 Medications     Ibuprofen      N (%)         character     66,887 (91.88%)"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a01_tables.html","id":"format-header","dir":"Articles","previous_headings":"format Functions","what":"2) Format Header","title":"Tables","text":"formatHeader() used create complex multi-level headers tables, making easy present grouped data clearly.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a01_tables.html","id":"header-levels","dir":"Articles","previous_headings":"format Functions > 2) Format Header","what":"Header levels","title":"Tables","text":"3 different levels headers, identified following keys: header: Custom labels correspond column names table values. header_name: Labels derived column names. Can omitted includeHeaderName =  FALSE. header_level: Labels derived values within columns set header. keys, together delimiter header levels (delim) used formatTable() format style gt flextable tables. Let’s create multi-level header strata columns, including three keys. show column names transformed: table formatting, won’t include header_name labels. Let’s see looks exclude :","code":"result |>   mutate(across(c(\"strata_name\", \"strata_level\"), ~ gsub(\"&&&\", \"and\", .x))) |>   formatHeader(     header = c(\"Stratifications\", \"strata_name\", \"strata_level\"),     delim = \"\\n\",     includeHeaderName = TRUE,     includeHeaderKey = TRUE   ) |>    colnames() #>  [1] \"result_id\"                                                                                                                                    #>  [2] \"cdm_name\"                                                                                                                                     #>  [3] \"group_name\"                                                                                                                                   #>  [4] \"group_level\"                                                                                                                                  #>  [5] \"variable_name\"                                                                                                                                #>  [6] \"variable_level\"                                                                                                                               #>  [7] \"estimate_name\"                                                                                                                                #>  [8] \"estimate_type\"                                                                                                                                #>  [9] \"additional_name\"                                                                                                                              #> [10] \"additional_level\"                                                                                                                             #> [11] \"[header]Stratifications\\n[header_name]strata_name\\n[header_level]age_group and sex\\n[header_name]strata_level\\n[header_level]<40 and Male\"    #> [12] \"[header]Stratifications\\n[header_name]strata_name\\n[header_level]age_group and sex\\n[header_name]strata_level\\n[header_level]>=40 and Male\"   #> [13] \"[header]Stratifications\\n[header_name]strata_name\\n[header_level]age_group and sex\\n[header_name]strata_level\\n[header_level]<40 and Female\"  #> [14] \"[header]Stratifications\\n[header_name]strata_name\\n[header_level]age_group and sex\\n[header_name]strata_level\\n[header_level]>=40 and Female\" result <- result |>   mutate(across(c(\"strata_name\", \"strata_level\"), ~ gsub(\"&&&\", \"and\", .x))) |>   formatHeader(     header = c(\"Stratifications\", \"strata_name\", \"strata_level\"),     delim = \"\\n\",     includeHeaderName = FALSE,     includeHeaderKey = TRUE   )    colnames(result) #>  [1] \"result_id\"                                                                               #>  [2] \"cdm_name\"                                                                                #>  [3] \"group_name\"                                                                              #>  [4] \"group_level\"                                                                             #>  [5] \"variable_name\"                                                                           #>  [6] \"variable_level\"                                                                          #>  [7] \"estimate_name\"                                                                           #>  [8] \"estimate_type\"                                                                           #>  [9] \"additional_name\"                                                                         #> [10] \"additional_level\"                                                                        #> [11] \"[header]Stratifications\\n[header_level]age_group and sex\\n[header_level]<40 and Male\"    #> [12] \"[header]Stratifications\\n[header_level]age_group and sex\\n[header_level]>=40 and Male\"   #> [13] \"[header]Stratifications\\n[header_level]age_group and sex\\n[header_level]<40 and Female\"  #> [14] \"[header]Stratifications\\n[header_level]age_group and sex\\n[header_level]>=40 and Female\""},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a01_tables.html","id":"format-table","dir":"Articles","previous_headings":"format Functions","what":"3) Format Table","title":"Tables","text":"formatTable() function final step formatting pipeline, formatted <data.frame> converted either <gt> <flextable>.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a01_tables.html","id":"prepare-data","dir":"Articles","previous_headings":"format Functions > 3) Format Table","what":"Prepare data","title":"Tables","text":"using formatTable(), ’ll tidy <data.frame> splitting group additional name-level columns (see vignette tidying <summarised_result>), drop unwanted columns:","code":"result <- result |>   splitGroup() |>   splitAdditional() |>   select(!c(\"result_id\", \"estimate_type\", \"cdm_name\")) head(result) #> # A tibble: 6 × 8 #>   cohort_name variable_name  variable_level estimate_name [header]Stratificati…¹ #>   <chr>       <chr>          <chr>          <chr>         <chr>                  #> 1 cohort1     number subjec… NA             N             3,203,857              #> 2 cohort2     number subjec… NA             N             7,353,196              #> 3 cohort1     age            NA             Mean (SD)     22.5563 (3.8918)       #> 4 cohort2     age            NA             Mean (SD)     68.0163 (0.6522)       #> 5 cohort1     Medications    Amoxiciline    N (%)         54,248 (92.00%)        #> 6 cohort2     Medications    Amoxiciline    N (%)         37,697 (71.83%)        #> # ℹ abbreviated name: #> #   ¹​`[header]Stratifications\\n[header_level]age_group and sex\\n[header_level]<40 and Male` #> # ℹ 3 more variables: #> #   `[header]Stratifications\\n[header_level]age_group and sex\\n[header_level]>=40 and Male` <chr>, #> #   `[header]Stratifications\\n[header_level]age_group and sex\\n[header_level]<40 and Female` <chr>, #> #   `[header]Stratifications\\n[header_level]age_group and sex\\n[header_level]>=40 and Female` <chr>"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a01_tables.html","id":"use-formattable","dir":"Articles","previous_headings":"format Functions > 3) Format Table","what":"Use formatTable()","title":"Tables","text":"Now data cleaned organized, formatTable() can used create well-structured <gt> <flextable> object. examples , used default style defined visOmopResults package (use gtStyle() flextableStyle() see styles). However, ’s possible customise appearance different parts table better suit needs.","code":"result |>   formatTable(     type = \"gt\",     delim = \"\\n\",     style = \"default\",     na = \"-\",     title = \"My formatted table!\",     subtitle = \"Created with the `visOmopResults` R package.\",     caption = NULL,     groupColumn = \"cohort_name\",     groupAsColumn = FALSE,     groupOrder = c(\"cohort2\", \"cohort1\"),     merge = \"variable_name\"   )"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a01_tables.html","id":"customising-table-styles","dir":"Articles","previous_headings":"format Functions > 3) Format Table","what":"customising Table Styles","title":"Tables","text":"Let’s start applying custom style <gt> table: creating similarly styled <flextable>, office R package required access specific formatting functions. formatted table! Created `visOmopResults` R package. cohort_name variable_name variable_level estimate_name Stratifications age_group sex <40 Male >=40 Male <40 Female >=40 Female cohort2   number subjects - N 7,353,196 1,959,567 9,805,397 7,415,215  age - Mean (SD) 68.0163 (0.6522) 49.8846 (3.5421) 64.1679 (8.2520) 66.0284 (2.7382)  Medications Amoxiciline N (%) 37,697 (71.83%) 55,991 (24.13%) 85,708 (54.70%) 38,481 (83.48%)   Ibuprofen N (%) 1,148 (16.46%) 88,825 (66.32%) 99,635 (85.66%) 50,019 (92.65%) cohort1   number subjects - N 3,203,857 4,023,282 1,956,698 4,035,381  age - Mean (SD) 22.5563 (3.8918) 30.0831 (4.6119) 63.6466 (3.1524) 47.9025 (1.7468)  Medications Amoxiciline N (%) 54,248 (92.00%) 54,460 (40.07%) 27,860 (21.32%) 44,670 (67.18%)   Ibuprofen N (%) 21,843 (56.69%) 41,836 (25.30%) 66,887 (91.88%) 50,765 (86.74%)","code":"result |>   formatTable(     type = \"gt\",     delim = \"\\n\",     style = list(       \"header\" = list(gt::cell_text(weight = \"bold\"),                        gt::cell_fill(color = \"orange\")),       \"header_level\" = list(gt::cell_text(weight = \"bold\"),                        gt::cell_fill(color = \"yellow\")),       \"column_name\" = gt::cell_text(weight = \"bold\"),       \"group_label\" = list(gt::cell_fill(color = \"blue\"),                            gt::cell_text(color = \"white\", weight = \"bold\")),       \"title\" = list(gt::cell_text(size = 20, weight = \"bold\")),       \"subtitle\" = list(gt::cell_text(size = 15)),       \"body\" = gt::cell_text(color = \"red\")     ),     na = \"-\",     title = \"My formatted table!\",     subtitle = \"Created with the `visOmopResults` R package.\",     caption = NULL,     groupColumn = \"cohort_name\",     groupAsColumn = FALSE,     groupOrder = c(\"cohort2\", \"cohort1\"),     merge = \"variable_name\"   ) result |>   formatTable(     type = \"flextable\",     delim = \"\\n\",     style = list(       \"header\" = list(         \"cell\" = officer::fp_cell(background.color = \"orange\"),         \"text\" = officer::fp_text(bold = TRUE)),       \"header_level\" = list(         \"cell\" = officer::fp_cell(background.color = \"yellow\"),         \"text\" = officer::fp_text(bold = TRUE)),       \"column_name\" = list(\"text\" = officer::fp_text(bold = TRUE)),       \"group_label\" = list(         \"cell\" = officer::fp_cell(background.color = \"blue\"),         \"text\" = officer::fp_text(bold = TRUE, color = \"white\")),       \"title\" = list(\"text\" = officer::fp_text(bold = TRUE, font.size = 20)),       \"subtitle\" = list(\"text\" = officer::fp_text(font.size = 15)),       \"body\" = list(\"text\" = officer::fp_text(color = \"red\"))     ),     na = \"-\",     title = \"My formatted table!\",     subtitle = \"Created with the `visOmopResults` R package.\",     caption = NULL,     groupColumn = \"cohort_name\",     groupAsColumn = FALSE,     groupOrder = c(\"cohort2\", \"cohort1\"),     merge = \"variable_name\"   )"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a02_plots.html","id":"plotting-with-a-summarised_result","dir":"Articles","previous_headings":"","what":"Plotting with a <summarised_result>","title":"Plots","text":"vignette, use penguins dataset palmerpenguins package. dataset summarised using PatientProfiles::summariseResult() function, aggregates data <summarised_result> format:","code":"library(PatientProfiles) library(palmerpenguins) library(dplyr)  summariseIsland <- function(island) {   penguins |>     filter(.data$island == .env$island) |>     summariseResult(       group = \"species\",       includeOverallGroup = TRUE,       strata = list(\"year\", \"sex\", c(\"year\", \"sex\")),       variables = c(         \"bill_length_mm\", \"bill_depth_mm\", \"flipper_length_mm\", \"body_mass_g\",          \"sex\"),       estimates = c(         \"median\", \"q25\", \"q75\", \"min\", \"max\", \"count_missing\", \"count\",          \"percentage\", \"density\")     ) |>     suppressMessages() |>     mutate(cdm_name = island) }  penguinsSummary <- bind(   summariseIsland(\"Torgersen\"),    summariseIsland(\"Biscoe\"),    summariseIsland(\"Dream\") )  penguinsSummary |> glimpse() #> Rows: 429,296 #> Columns: 13 #> $ result_id        <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,… #> $ cdm_name         <chr> \"Torgersen\", \"Torgersen\", \"Torgersen\", \"Torgersen\", \"… #> $ group_name       <chr> \"overall\", \"overall\", \"overall\", \"overall\", \"overall\"… #> $ group_level      <chr> \"overall\", \"overall\", \"overall\", \"overall\", \"overall\"… #> $ strata_name      <chr> \"overall\", \"overall\", \"overall\", \"overall\", \"overall\"… #> $ strata_level     <chr> \"overall\", \"overall\", \"overall\", \"overall\", \"overall\"… #> $ variable_name    <chr> \"number records\", \"bill_length_mm\", \"bill_length_mm\",… #> $ variable_level   <chr> NA, NA, NA, NA, NA, NA, NA, \"density_001\", \"density_0… #> $ estimate_name    <chr> \"count\", \"median\", \"q25\", \"q75\", \"min\", \"max\", \"count… #> $ estimate_type    <chr> \"integer\", \"numeric\", \"numeric\", \"numeric\", \"numeric\"… #> $ estimate_value   <chr> \"52\", \"38.9\", \"36.65\", \"41.1\", \"33.5\", \"46\", \"1\", \"29… #> $ additional_name  <chr> \"overall\", \"overall\", \"overall\", \"overall\", \"overall\"… #> $ additional_level <chr> \"overall\", \"overall\", \"overall\", \"overall\", \"overall\"…"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a02_plots.html","id":"plotting-principles-for-summarised_result-objects","dir":"Articles","previous_headings":"Plotting with a <summarised_result>","what":"Plotting principles for <summarised_result> objects","title":"Plots","text":"1) Tidy Format working <summarised_result> objects, data internally converted tidy format plotting. important distinction columns strata_name strata_level original <summarised_result> used directly plotting functions. Instead, tidy columns referenced. information tidy format, refer omopgenerics package vignette <summarised_result> . identify available tidy columns, use tidyColumns() function: 2) Subsetting Variables calling plotting functions, always subset <summarised_result> object variable interest. Avoid combining results unrelated variables, may lead NA values tidy format, can affect plots.","code":"tidyColumns(penguinsSummary) #>  [1] \"cdm_name\"       \"species\"        \"year\"           \"sex\"            #>  [5] \"variable_name\"  \"variable_level\" \"count\"          \"median\"         #>  [9] \"q25\"            \"q75\"            \"min\"            \"max\"            #> [13] \"count_missing\"  \"density_x\"      \"density_y\"      \"percentage\""},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a02_plots.html","id":"scatter-plot","dir":"Articles","previous_headings":"Plotting with a <summarised_result>","what":"Scatter plot","title":"Plots","text":"can create simple scatter plots using plotScatter() let’s see examples:  Additionally, can use function themeVisOmop() change default ggplot2 style default style. , can use standard ggplot2 functionalities returned plot:","code":"penguinsSummary |>   filter(variable_name == \"bill_depth_mm\") |>   filterStrata(year != \"overall\", sex == \"overall\") |>   scatterPlot(     x = \"year\",      y = \"median\",     line = TRUE,      point = TRUE,     ribbon = FALSE,     facet = \"cdm_name\",     colour = \"species\"   ) penguinsSummary |>   filter(variable_name %in% c(\"bill_length_mm\", \"bill_depth_mm\"))|>   filterStrata(year == \"overall\", sex == \"overall\") |>   filterGroup(species != \"overall\") |>   scatterPlot(     x = \"density_x\",      y = \"density_y\",     line = TRUE,      point = FALSE,     ribbon = FALSE,     facet = cdm_name ~ variable_name,     colour = \"species\"   ) +   themeVisOmop() +   ggplot2::facet_grid(cdm_name ~ variable_name, scales = \"free_x\") penguinsSummary |>   filter(variable_name == \"flipper_length_mm\") |>   filterStrata(year != \"overall\", sex %in% c(\"female\", \"male\")) |>   scatterPlot(     x = c(\"year\", \"sex\"),      y = \"median\",     ymin = \"q25\",     ymax = \"q75\",     line = FALSE,      point = TRUE,     ribbon = FALSE,     facet = cdm_name ~ species,     colour = \"sex\",     group = c(\"year\", \"sex\")   )  +   themeVisOmop() +   ggplot2::coord_flip() +   ggplot2::labs(y = \"Flipper length (mm)\") +    ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 90, vjust = 0.5, hjust=1)) penguinsSummary |>   filter(     variable_name %in% c(\"flipper_length_mm\", \"bill_length_mm\", \"bill_depth_mm\")   ) |>   filterStrata(sex == \"overall\") |>   scatterPlot(     x = \"year\",      y = \"median\",     ymin = \"min\",     ymax = \"max\",     line = FALSE,      point = TRUE,     ribbon = TRUE,     facet = cdm_name ~ species,     colour = \"variable_name\",     group = c(\"variable_name\")   ) +   themeVisOmop(fontsizeRef = 12) +    ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 90, vjust = 0.5, hjust=1))"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a02_plots.html","id":"bar-plot","dir":"Articles","previous_headings":"Plotting with a <summarised_result>","what":"Bar plot","title":"Plots","text":"Let’s create bar plots:","code":"penguinsSummary |>   filter(variable_name == \"number records\") |>   filterGroup(species != \"overall\") |>   filterStrata(sex != \"overall\", year != \"overall\") |>   barPlot(     x = \"year\",     y = \"count\",     colour = \"sex\",     facet = cdm_name ~ species   ) +   themeVisOmop(fontsizeRef = 12)"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a02_plots.html","id":"box-plot","dir":"Articles","previous_headings":"Plotting with a <summarised_result>","what":"Box plot","title":"Plots","text":"Let’s create box plots body mass:   Note didnt specify x levels x axis, box plots produced anyway.","code":"penguinsSummary |>   filter(variable_name == \"body_mass_g\") |>   boxPlot(x = \"year\", facet = species ~ cdm_name, colour = \"sex\") +   themeVisOmop() penguinsSummary |>   filter(variable_name == \"body_mass_g\") |>   filterGroup(species != \"overall\") |>   filterStrata(sex %in% c(\"female\", \"male\"), year != \"overall\") |>   boxPlot(x = \"cdm_name\", facet = c(\"sex\", \"species\"), colour = \"year\") +   themeVisOmop(fontsizeRef = 11)"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a02_plots.html","id":"plotting-with-a-data-frame","dir":"Articles","previous_headings":"","what":"Plotting with a <data.frame>","title":"Plots","text":"Plotting functions can also used usual <data.frame>. case use tidy format penguinsSummary. Using tidy format, can replicate plots. instance, recreate previous example:","code":"penguinsTidy <- penguinsSummary |>   filter(!estimate_name %in% c(\"density_x\", \"density_y\")) |> # remove density for simplicity   tidy() penguinsTidy |> glimpse() #> Rows: 720 #> Columns: 14 #> $ cdm_name       <chr> \"Torgersen\", \"Torgersen\", \"Torgersen\", \"Torgersen\", \"To… #> $ species        <chr> \"overall\", \"overall\", \"overall\", \"overall\", \"overall\", … #> $ year           <chr> \"overall\", \"overall\", \"overall\", \"overall\", \"overall\", … #> $ sex            <chr> \"overall\", \"overall\", \"overall\", \"overall\", \"overall\", … #> $ variable_name  <chr> \"number records\", \"bill_length_mm\", \"bill_depth_mm\", \"f… #> $ variable_level <chr> NA, NA, NA, NA, NA, \"female\", \"male\", NA, NA, NA, NA, N… #> $ count          <int> 52, NA, NA, NA, NA, 24, 23, 5, 20, 16, 16, NA, NA, NA, … #> $ median         <int> NA, 38, 18, 191, 3700, NA, NA, NA, NA, NA, NA, 38, 38, … #> $ q25            <int> NA, 36, 17, 187, 3338, NA, NA, NA, NA, NA, NA, 37, 35, … #> $ q75            <int> NA, 41, 19, 195, 4000, NA, NA, NA, NA, NA, NA, 39, 41, … #> $ min            <int> NA, 33, 15, 176, 2900, NA, NA, NA, NA, NA, NA, 34, 33, … #> $ max            <int> NA, 46, 21, 210, 4700, NA, NA, NA, NA, NA, NA, 46, 45, … #> $ count_missing  <int> NA, 1, 1, 1, 1, NA, NA, NA, NA, NA, NA, 1, 0, 0, 1, 0, … #> $ percentage     <dbl> NA, NA, NA, NA, NA, 46.153846, 44.230769, 9.615385, NA,… penguinsTidy |>   filter(     variable_name == \"body_mass_g\",     species != \"overall\",     sex %in% c(\"female\", \"male\"),     year != \"overall\"   ) |>   boxPlot(x = \"cdm_name\", facet = sex ~ species, colour = \"year\") +   themeVisOmop()"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a02_plots.html","id":"custom-plotting","dir":"Articles","previous_headings":"","what":"Custom plotting","title":"Plots","text":"tidy format useful apply custom ggplot2 function may interested :","code":"library(ggplot2) penguinsSummary |>   filter(variable_name == \"number records\") |>   tidy() |>   ggplot(aes(x = year, y = sex, fill = count, label = count)) +   themeVisOmop() +   geom_tile() +   scale_fill_viridis_c(trans = \"log\") +    geom_text() +   facet_grid(cdm_name ~ species) +    ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 90, vjust = 0.5, hjust=1))"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a02_plots.html","id":"combine-with-ggplot2","dir":"Articles","previous_headings":"","what":"Combine with ggplot2","title":"Plots","text":"plotting functions wrapper around ggplot2 package, outputs plotting functions can later customised ggplot2 similar tools. example can use ggplot2::labs() change labels ggplot2::theme() move location legend.  can also use ggplot2::ggsave() later save one plots ‘.png’ file.","code":"penguinsSummary |>   filter(     group_level != \"overall\",     strata_name == \"year &&& sex\",     !grepl(\"NA\", strata_level),     variable_name == \"body_mass_g\") |>   boxPlot(x = \"species\", facet = cdm_name ~ sex, colour = \"year\") +   themeVisOmop(fontsizeRef = 12) +   ylim(c(0, 6500)) +   labs(x = \"My custom x label\") ggsave(   \"figure8.png\", plot = last_plot(), device = \"png\", width = 15, height = 12,    units = \"cm\", dpi = 300)"},{"path":"https://darwin-eu.github.io/visOmopResults/articles/a02_plots.html","id":"combine-with-plotly","dir":"Articles","previous_headings":"","what":"Combine with plotly","title":"Plots","text":"Although package currently provide plotly functionality ggplots can easily converted <plotly> ones using function plotly::ggplotly(). can make interactivity plots better.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Martí Català. Author. Núria Mercadé-Besora. Author, maintainer. Yuchen Guo. Contributor. Elin Rowlands. Contributor. Edward Burn. Contributor.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Català M, Mercadé-Besora N (2025). visOmopResults: Graphs Tables OMOP Results. R package version 1.0.0, https://github.com/darwin-eu/visOmopResults, https://darwin-eu.github.io/visOmopResults/.","code":"@Manual{,   title = {visOmopResults: Graphs and Tables for OMOP Results},   author = {Martí Català and Núria Mercadé-Besora},   year = {2025},   note = {R package version 1.0.0, https://github.com/darwin-eu/visOmopResults},   url = {https://darwin-eu.github.io/visOmopResults/}, }"},{"path":[]},{"path":"https://darwin-eu.github.io/visOmopResults/index.html","id":"package-overview","dir":"","previous_headings":"","what":"Package overview","title":"Graphs and Tables for OMOP Results","text":"visOmopResults offers set functions tailored format objects class <summarised_result> (defined omopgenerics package). provides functionalities create formatted tables generate plots. visualisations highly versatile reporting results Shiny apps, RMarkdown, Quarto, , supporting various output formats HTML, PNG, Word, PDF.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/index.html","id":"lets-get-started","dir":"","previous_headings":"","what":"Let’s get started","title":"Graphs and Tables for OMOP Results","text":"can install latest version visOmopResults CRAN: can install development version GitHub : <summarised_result> standardised output format utilized across various packages, including: CohortCharacteristics DrugUtilisation IncidencePrevalence PatientProfiles CodelistGenerator CohortSurvival CohortSymmetry Although standard output format essential, can sometimes challenging manage. visOmopResults package aims simplify process. demonstrate package’s functionality, let’s start using mock results:","code":"install.packages(\"visOmopResults\") # install.packages(\"pak\") pak::pkg_install(\"darwin-eu/visOmopResults\") library(visOmopResults) result <- mockSummarisedResult()"},{"path":"https://darwin-eu.github.io/visOmopResults/index.html","id":"tables-visualisations","dir":"","previous_headings":"","what":"Tables visualisations","title":"Graphs and Tables for OMOP Results","text":"Currently table functionalities built around 4 packages: tibble, gt, flextable, datatable. two main functions: visOmopTable(): Creates well-formatted table specifically <summarised_result> object. visTable(): Creates nicely formatted table <data.frame> object. Let’s see simple example:","code":"result |>   filterStrata(sex != \"overall\" & age_group != \"overall\") |>   visOmopTable(     type = \"flextable\",     estimateName = c(       \"N(%)\" = \"<count> (<percentage>%)\",        \"N\" = \"<count>\",        \"mean (sd)\" = \"<mean> (<sd>)\"),     header = c(\"sex\", \"age_group\"),     settingsColumn = NULL,     groupColumn = c(\"cohort_name\"),     rename = c(\"Variable\" = \"variable_name\", \" \" = \"variable_level\"),     hide = \"cdm_name\"   )"},{"path":"https://darwin-eu.github.io/visOmopResults/index.html","id":"plots-visualisations","dir":"","previous_headings":"","what":"Plots visualisations","title":"Graphs and Tables for OMOP Results","text":"Currently plot functionalities built around ggplot2. output plot functions <ggplot2> object can customised. three plotting functions: plotScatter() create scatter plot. plotBar() create bar plot. plotBox() create box plot. Additionally, themeVisOmop() function applies consistent styling plots, aligning package’s visual design. Let’s see can create simple boxplot age:","code":"library(dplyr) result |>   filter(variable_name == \"number subjects\") |>   filterStrata(sex != \"overall\") |>   barPlot(x = \"age_group\",            y = \"count\",           facet = \"cohort_name\",            colour = \"sex\") +   themeVisOmop(fontsizeRef = 12)"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/barPlot.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a bar plot visualisation from a <summarised_result> object — barPlot","title":"Create a bar plot visualisation from a <summarised_result> object — barPlot","text":"Create bar plot visualisation <summarised_result> object","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/barPlot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a bar plot visualisation from a <summarised_result> object — barPlot","text":"","code":"barPlot(   result,   x,   y,   width = NULL,   just = 0.5,   facet = NULL,   colour = NULL,   label = character() )"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/barPlot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a bar plot visualisation from a <summarised_result> object — barPlot","text":"result <summarised_result> object. x Column estimate name used x variable. y Column estimate name used y variable. width Bar width, geom_col() ggplot2 package. just Adjustment column placement, geom_col() ggplot2 package. facet Variables facet , formula can provided specify variables used rows ones columns. colour Columns use determine colors. label Character vector columns display interactively plotly.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/barPlot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a bar plot visualisation from a <summarised_result> object — barPlot","text":"plot object.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/barPlot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a bar plot visualisation from a <summarised_result> object — barPlot","text":"","code":"result <- mockSummarisedResult() |> dplyr::filter(variable_name == \"age\")  barPlot(   result = result,   x = \"cohort_name\",   y = \"mean\",   facet = c(\"age_group\", \"sex\"),   colour = \"sex\")"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/boxPlot.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a box plot visualisation from a <summarised_result> object — boxPlot","title":"Create a box plot visualisation from a <summarised_result> object — boxPlot","text":"Create box plot visualisation <summarised_result> object","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/boxPlot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a box plot visualisation from a <summarised_result> object — boxPlot","text":"","code":"boxPlot(   result,   x,   lower = \"q25\",   middle = \"median\",   upper = \"q75\",   ymin = \"min\",   ymax = \"max\",   facet = NULL,   colour = NULL,   label = character() )"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/boxPlot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a box plot visualisation from a <summarised_result> object — boxPlot","text":"result <summarised_result> object. x Columns use x axes. lower Estimate name lower quantile box. middle Estimate name middle line box. upper Estimate name upper quantile box. ymin Estimate name lower limit bars. ymax Estimate name upper limit bars. facet Variables facet , formula can provided specify variables used rows ones columns. colour Columns use determine colors. label Character vector columns display interactively plotly.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/boxPlot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a box plot visualisation from a <summarised_result> object — boxPlot","text":"ggplot2 object.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/boxPlot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a box plot visualisation from a <summarised_result> object — boxPlot","text":"","code":"dplyr::tibble(year = \"2000\", q25 = 25, median = 50, q75 = 75, min = 0, max = 100) |>   boxPlot(x = \"year\")"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/customiseText.html","id":null,"dir":"Reference","previous_headings":"","what":"Apply styling to text or column names — customiseText","title":"Apply styling to text or column names — customiseText","text":"function styles character vectors column names data frame. styling function can customised, can provide specific replacements certain values.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/customiseText.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Apply styling to text or column names — customiseText","text":"","code":"customiseText(   x,   fun = function(x) stringr::str_to_sentence(gsub(\"_\", \" \", x)),   custom = NULL,   keep = NULL )"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/customiseText.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Apply styling to text or column names — customiseText","text":"x character vector style text. fun styling function apply text x. default function converts snake_case sentence case. custom named character vector indicating custom names specific values x. NULL, styling function fun applied values. keep Either character vector names keep unchanged. NULL, names styled.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/customiseText.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Apply styling to text or column names — customiseText","text":"character vector styled text data frame styled column names.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/customiseText.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Apply styling to text or column names — customiseText","text":"","code":"# Styling a character vector customiseText(c(\"some_column_name\", \"another_column\")) #> [1] \"Some column name\" \"Another column\"    # Custom styling for specific values customiseText(x = c(\"some_column\", \"another_column\"),           custom = c(\"Custom Name\" = \"another_column\")) #> [1] \"Some column\" \"Custom Name\"  # Keeping specific values unchanged customiseText(x = c(\"some_column\", \"another_column\"), keep = \"another_column\") #> [1] \"Some column\"    \"another_column\"  # Styling column names and variables in a data frame dplyr::tibble(   some_column = c(\"hi_there\", \"rename_me\", \"example\", \"to_keep\"),   another_column = 1:4,   to_keep = \"as_is\" ) |>   dplyr::mutate(     \"some_column\" = customiseText(some_column, custom = c(\"EXAMPLE\" = \"example\"), keep = \"to_keep\")   ) |>   dplyr::rename_with(.fn = ~ customiseText(.x, keep = \"to_keep\")) #> # A tibble: 4 × 3 #>   `Some column` `Another column` to_keep #>   <chr>                    <int> <chr>   #> 1 Hi there                     1 as_is   #> 2 Rename me                    2 as_is   #> 3 EXAMPLE                      3 as_is   #> 4 to_keep                      4 as_is"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/emptyPlot.html","id":null,"dir":"Reference","previous_headings":"","what":"Returns an empty plot — emptyPlot","title":"Returns an empty plot — emptyPlot","text":"Returns empty plot","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/emptyPlot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Returns an empty plot — emptyPlot","text":"","code":"emptyPlot()"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/emptyPlot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Returns an empty plot — emptyPlot","text":"empty ggplot object","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/emptyPlot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Returns an empty plot — emptyPlot","text":"","code":"emptyPlot()"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/emptyTable.html","id":null,"dir":"Reference","previous_headings":"","what":"Returns an empty table — emptyTable","title":"Returns an empty table — emptyTable","text":"Returns empty table","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/emptyTable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Returns an empty table — emptyTable","text":"","code":"emptyTable(type = \"gt\")"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/emptyTable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Returns an empty table — emptyTable","text":"type desired format output table. See tableType() allowed options.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/emptyTable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Returns an empty table — emptyTable","text":"empty table class specified type","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/emptyTable.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Returns an empty table — emptyTable","text":"Table data","code":"emptyTable(type = \"flextable\") .cl-2e0f9638{}.cl-2e09375c{font-family:'DejaVu Sans';font-size:11pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-2e0c7fca{margin:0;text-align:right;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-2e0c9960{width:1.5in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}Table has no data"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatEstimateName.html","id":null,"dir":"Reference","previous_headings":"","what":"Formats estimate_name and estimate_value column — formatEstimateName","title":"Formats estimate_name and estimate_value column — formatEstimateName","text":"Formats estimate_name estimate_value columns changing name estimate name /joining different estimates together single row.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatEstimateName.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Formats estimate_name and estimate_value column — formatEstimateName","text":"","code":"formatEstimateName(   result,   estimateName = NULL,   keepNotFormatted = TRUE,   useFormatOrder = TRUE )"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatEstimateName.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Formats estimate_name and estimate_value column — formatEstimateName","text":"result <summarised_result>. estimateName Named list estimate name's join, sorted computation order. Indicate estimate_name's <...>. keepNotFormatted Whether keep rows formatted. useFormatOrder Whether use order estimate names appear estimateName (TRUE), use order input dataframe (FALSE).","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatEstimateName.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Formats estimate_name and estimate_value column — formatEstimateName","text":"<summarised_result> object.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatEstimateName.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Formats estimate_name and estimate_value column — formatEstimateName","text":"","code":"result <- mockSummarisedResult() result |>   formatEstimateName(     estimateName = c(       \"N (%)\" = \"<count> (<percentage>%)\", \"N\" = \"<count>\"     ),     keepNotFormatted = FALSE   ) #> # A tibble: 54 × 13 #>    result_id cdm_name group_name  group_level strata_name       strata_level    #>        <int> <chr>    <chr>       <chr>       <chr>             <chr>           #>  1         1 mock     cohort_name cohort1     overall           overall         #>  2         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Male    #>  3         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Male   #>  4         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Female  #>  5         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Female #>  6         1 mock     cohort_name cohort1     sex               Male            #>  7         1 mock     cohort_name cohort1     sex               Female          #>  8         1 mock     cohort_name cohort1     age_group         <40             #>  9         1 mock     cohort_name cohort1     age_group         >=40            #> 10         1 mock     cohort_name cohort2     overall           overall         #> # ℹ 44 more rows #> # ℹ 7 more variables: variable_name <chr>, variable_level <chr>, #> #   estimate_name <chr>, estimate_type <chr>, estimate_value <chr>, #> #   additional_name <chr>, additional_level <chr>"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatEstimateValue.html","id":null,"dir":"Reference","previous_headings":"","what":"Formats the estimate_value column — formatEstimateValue","title":"Formats the estimate_value column — formatEstimateValue","text":"Formats estimate_value column <summarised_result> object editing number decimals, decimal thousand/millions separator marks.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatEstimateValue.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Formats the estimate_value column — formatEstimateValue","text":"","code":"formatEstimateValue(   result,   decimals = c(integer = 0, numeric = 2, percentage = 1, proportion = 3),   decimalMark = \".\",   bigMark = \",\" )"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatEstimateValue.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Formats the estimate_value column — formatEstimateValue","text":"result <summarised_result>. decimals Number decimals per estimate type (integer, numeric, percentage, proportion), estimate name, estimate values (introduce number decimals). decimalMark Decimal separator mark. bigMark Thousand millions separator mark.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatEstimateValue.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Formats the estimate_value column — formatEstimateValue","text":"<summarised_result>.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatEstimateValue.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Formats the estimate_value column — formatEstimateValue","text":"","code":"result <- mockSummarisedResult()  result |> formatEstimateValue(decimals = 1) #> # A tibble: 126 × 13 #>    result_id cdm_name group_name  group_level strata_name       strata_level    #>        <int> <chr>    <chr>       <chr>       <chr>             <chr>           #>  1         1 mock     cohort_name cohort1     overall           overall         #>  2         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Male    #>  3         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Male   #>  4         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Female  #>  5         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Female #>  6         1 mock     cohort_name cohort1     sex               Male            #>  7         1 mock     cohort_name cohort1     sex               Female          #>  8         1 mock     cohort_name cohort1     age_group         <40             #>  9         1 mock     cohort_name cohort1     age_group         >=40            #> 10         1 mock     cohort_name cohort2     overall           overall         #> # ℹ 116 more rows #> # ℹ 7 more variables: variable_name <chr>, variable_level <chr>, #> #   estimate_name <chr>, estimate_type <chr>, estimate_value <chr>, #> #   additional_name <chr>, additional_level <chr>  result |> formatEstimateValue(decimals = c(integer = 0, numeric = 1)) #> # A tibble: 126 × 13 #>    result_id cdm_name group_name  group_level strata_name       strata_level    #>        <int> <chr>    <chr>       <chr>       <chr>             <chr>           #>  1         1 mock     cohort_name cohort1     overall           overall         #>  2         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Male    #>  3         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Male   #>  4         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Female  #>  5         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Female #>  6         1 mock     cohort_name cohort1     sex               Male            #>  7         1 mock     cohort_name cohort1     sex               Female          #>  8         1 mock     cohort_name cohort1     age_group         <40             #>  9         1 mock     cohort_name cohort1     age_group         >=40            #> 10         1 mock     cohort_name cohort2     overall           overall         #> # ℹ 116 more rows #> # ℹ 7 more variables: variable_name <chr>, variable_level <chr>, #> #   estimate_name <chr>, estimate_type <chr>, estimate_value <chr>, #> #   additional_name <chr>, additional_level <chr>  result |>   formatEstimateValue(decimals = c(numeric = 1, count = 0)) #> # A tibble: 126 × 13 #>    result_id cdm_name group_name  group_level strata_name       strata_level    #>        <int> <chr>    <chr>       <chr>       <chr>             <chr>           #>  1         1 mock     cohort_name cohort1     overall           overall         #>  2         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Male    #>  3         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Male   #>  4         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Female  #>  5         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Female #>  6         1 mock     cohort_name cohort1     sex               Male            #>  7         1 mock     cohort_name cohort1     sex               Female          #>  8         1 mock     cohort_name cohort1     age_group         <40             #>  9         1 mock     cohort_name cohort1     age_group         >=40            #> 10         1 mock     cohort_name cohort2     overall           overall         #> # ℹ 116 more rows #> # ℹ 7 more variables: variable_name <chr>, variable_level <chr>, #> #   estimate_name <chr>, estimate_type <chr>, estimate_value <chr>, #> #   additional_name <chr>, additional_level <chr>"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatHeader.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a header for gt and flextable objects — formatHeader","title":"Create a header for gt and flextable objects — formatHeader","text":"Pivots <summarised_result> object based column names header, generating specific column names subsequent header formatting formatTable function.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatHeader.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a header for gt and flextable objects — formatHeader","text":"","code":"formatHeader(   result,   header,   delim = \"\\n\",   includeHeaderName = TRUE,   includeHeaderKey = TRUE )"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatHeader.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a header for gt and flextable objects — formatHeader","text":"result <summarised_result>. header Names variables make headers. delim Delimiter use separate headers. includeHeaderName Whether include column name header. includeHeaderKey Whether include header key (header, header_name, header_level) header type column names.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatHeader.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a header for gt and flextable objects — formatHeader","text":"tibble rows pivotted columns key names subsequent header formatting.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatHeader.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a header for gt and flextable objects — formatHeader","text":"","code":"result <- mockSummarisedResult()  result |>   formatHeader(     header = c(       \"Study cohorts\", \"group_level\", \"Study strata\", \"strata_name\",       \"strata_level\"     ),     includeHeaderName = FALSE   ) #> # A tibble: 7 × 27 #>   result_id cdm_name group_name  variable_name   variable_level estimate_name #>       <int> <chr>    <chr>       <chr>           <chr>          <chr>         #> 1         1 mock     cohort_name number subjects NA             count         #> 2         1 mock     cohort_name age             NA             mean          #> 3         1 mock     cohort_name age             NA             sd            #> 4         1 mock     cohort_name Medications     Amoxiciline    count         #> 5         1 mock     cohort_name Medications     Amoxiciline    percentage    #> 6         1 mock     cohort_name Medications     Ibuprofen      count         #> 7         1 mock     cohort_name Medications     Ibuprofen      percentage    #> # ℹ 21 more variables: estimate_type <chr>, additional_name <chr>, #> #   additional_level <chr>, #> #   `[header]Study cohorts\\n[header_level]cohort1\\n[header]Study strata\\n[header_level]overall\\n[header_level]overall` <chr>, #> #   `[header]Study cohorts\\n[header_level]cohort1\\n[header]Study strata\\n[header_level]age_group &&& sex\\n[header_level]<40 &&& Male` <chr>, #> #   `[header]Study cohorts\\n[header_level]cohort1\\n[header]Study strata\\n[header_level]age_group &&& sex\\n[header_level]>=40 &&& Male` <chr>, #> #   `[header]Study cohorts\\n[header_level]cohort1\\n[header]Study strata\\n[header_level]age_group &&& sex\\n[header_level]<40 &&& Female` <chr>, #> #   `[header]Study cohorts\\n[header_level]cohort1\\n[header]Study strata\\n[header_level]age_group &&& sex\\n[header_level]>=40 &&& Female` <chr>, …"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatTable.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a flextable or gt object from a dataframe — formatTable","title":"Creates a flextable or gt object from a dataframe — formatTable","text":"Creates flextable object dataframe using delimiter span header, allows easily customise table style.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatTable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a flextable or gt object from a dataframe — formatTable","text":"","code":"formatTable(   x,   type = \"gt\",   delim = \"\\n\",   style = \"default\",   na = \"-\",   title = NULL,   subtitle = NULL,   caption = NULL,   groupColumn = NULL,   groupAsColumn = FALSE,   groupOrder = NULL,   merge = NULL )"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatTable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a flextable or gt object from a dataframe — formatTable","text":"x dataframe. type desired format output table. See tableType() allowed options. \"tibble\", formatting applied. delim Delimiter. style Named list specifies style different parts gt flextable table generated. Accepted style entries : title, subtitle, header, header_name, header_level, column_name, group_label, body. Alternatively, use \"default\" get visOmopResults style, NULL gt/flextable style. Keep mind styling code different gt flextable. see \"deafult\" style code use tableStyle(). na display missing values. used \"datatable\". title Title table, NULL title. used \"datatable\". subtitle Subtitle table, NULL subtitle. used \"datatable\". caption Caption table, NULL caption. Text markdown formatting style (e.g. *caption * caption italics). groupColumn Specifies columns use group labels. default, new group name combination column names, joined \"_\". assign custom group name, provide named list : list(newGroupName = c(\"variable_name\", \"variable_level\")) groupAsColumn Whether display group labels column (TRUE) rows (FALSE). used \"datatable\". groupOrder Order display group labels. used \"datatable\". merge Names columns merge vertically consecutive row cells identical values. Alternatively, use \"all_columns\" apply merging columns, use NULL indicate merging. used \"datatable\".","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatTable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a flextable or gt object from a dataframe — formatTable","text":"flextable object. flextable gt object.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/formatTable.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a flextable or gt object from a dataframe — formatTable","text":"fxTable example group_level result_id cdm_name group_name variable_name variable_level estimate_name estimate_type additional_name additional_level Study strata overall age_group &&& sex sex age_group overall <40 &&& Male >=40 &&& Male <40 &&& Female >=40 &&& Female Male Female <40 >=40 cohort1 1 mock cohort_name number subjects -- count integer overall overall 1,333,485 9,272,818 8,941,227 2,036,644 2,569,829 6,140,056 4,414,992 3,155,947 1,013,138    age -- mean numeric overall overall 26.2 41.6 43.9 18.2 7.8 1.8 72.8 97.1 53.5      sd numeric overall overall 9.6 4.5 9.8 5.4 3.6 5.0 0.7 9.7 6.5    Medications Amoxiciline count integer overall overall 45,675 17,903 96,621 71,341 2,489 62,646 82,792 64,307 70,848      percentage percentage overall overall 0.865807477384806 43.0898792576045 72.493509715423 41.2256387062371 55.0862395204604 15.6360570108518 4.30012932047248 68.464411306195 51.4402497094125     Ibuprofen count integer overall overall 34,970 98,267 40,885 36,087 65,251 14,356 68,080 85,929 83,863      percentage percentage overall overall 11.3047500839457 97.0262279734015 64.8082781815901 5.6073043262586 47.3137095803395 29.4625013135374 61.0299621941522 12.1108880266547 62.9416507901624 cohort2 1 mock cohort_name number subjects -- count integer overall overall 2,726,462 6,536,994 9,278,701 266,247 5,594,912 8,541,737 758,830 2,058,289 4,958,896    age -- mean numeric overall overall 16.6 5.8 45.9 62.3 59.5 74.3 52.4 49.7 1.5      sd numeric overall overall 9.8 5.4 7.6 5.6 7.8 6.4 3.8 3.6 8.4    Medications Amoxiciline count integer overall overall 87,073 28,181 17,322 10,967 58,622 85,072 92,153 67,566 35,059      percentage percentage overall overall 94.568784837611 84.309694217518 6.48830933496356 76.2110914569348 7.83842522650957 13.3507662685588 80.9696201002225 55.9383239364251 73.3729686122388     Ibuprofen count integer overall overall 88,131 23,770 57,863 89,790 34,443 76,086 73,110 85,243 97,582      percentage percentage overall overall 71.1955302860588 61.2082786625251 3.44292330555618 66.5890787029639 65.2967276517302 45.1858439715579 51.6804101876915 67.6610797178 88.0933094071224","code":"# Example 1 mockSummarisedResult() |>   formatEstimateValue(decimals = c(integer = 0, numeric = 1)) |>   formatHeader(     header = c(\"Study strata\", \"strata_name\", \"strata_level\"),     includeHeaderName = FALSE   ) |>   formatTable(     type = \"flextable\",     style = \"default\",     na = \"--\",     title = \"fxTable example\",     subtitle = NULL,     caption = NULL,     groupColumn = \"group_level\",     groupAsColumn = TRUE,     groupOrder = c(\"cohort1\", \"cohort2\"),     merge = \"all_columns\"   ) .cl-2f21f728{}.cl-2f1a0efa{font-family:'Arial';font-size:15pt;font-weight:bold;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-2f1a0f04{font-family:'Arial';font-size:10pt;font-weight:bold;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-2f1a0f0e{font-family:'DejaVu Sans';font-size:11pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-2f1cedd2{margin:0;text-align:center;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-2f1ceddc{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-2f1cede6{margin:0;text-align:right;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-2f1d1014{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.2pt solid rgba(190, 190, 190, 1.00);border-top: 1.2pt solid rgba(190, 190, 190, 1.00);border-left: 1.2pt solid rgba(190, 190, 190, 1.00);border-right: 1.2pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-2f1d101e{width:0.75in;background-color:rgba(200, 200, 200, 1.00);vertical-align: middle;border-bottom: 1.2pt solid rgba(190, 190, 190, 1.00);border-top: 1.2pt solid rgba(190, 190, 190, 1.00);border-left: 1.2pt solid rgba(190, 190, 190, 1.00);border-right: 1.2pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-2f1d101f{width:0.75in;background-color:rgba(225, 225, 225, 1.00);vertical-align: middle;border-bottom: 1.2pt solid rgba(190, 190, 190, 1.00);border-top: 1.2pt solid rgba(190, 190, 190, 1.00);border-left: 1.2pt solid rgba(190, 190, 190, 1.00);border-right: 1.2pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-2f1d1020{width:0.75in;background-color:rgba(233, 233, 233, 1.00);vertical-align: middle;border-bottom: 1pt solid rgba(190, 190, 190, 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solid rgba(0, 0, 0, 1.00);border-right: 1pt solid rgba(190, 190, 190, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}fxTable examplegroup_levelresult_idcdm_namegroup_namevariable_namevariable_levelestimate_nameestimate_typeadditional_nameadditional_levelStudy strataoverallage_group &&& sexsexage_groupoverall<40 &&& Male>=40 &&& Male<40 &&& Female>=40 &&& FemaleMaleFemale<40>=40cohort11mockcohort_namenumber subjects--countintegeroveralloverall1,333,4859,272,8188,941,2272,036,6442,569,8296,140,0564,414,9923,155,9471,013,138age--meannumericoveralloverall26.241.643.918.27.81.872.897.153.5sdnumericoveralloverall9.64.59.85.43.65.00.79.76.5MedicationsAmoxicilinecountintegeroveralloverall45,67517,90396,62171,3412,48962,64682,79264,30770,848percentagepercentageoveralloverall0.86580747738480643.089879257604572.49350971542341.225638706237155.086239520460415.63605701085184.3001293204724868.46441130619551.4402497094125Ibuprofencountintegeroveralloverall34,97098,26740,88536,08765,25114,35668,08085,92983,863percentagepercentageoveralloverall11.304750083945797.026227973401564.80827818159015.607304326258647.313709580339529.462501313537461.029962194152212.110888026654762.9416507901624cohort21mockcohort_namenumber subjects--countintegeroveralloverall2,726,4626,536,9949,278,701266,2475,594,9128,541,737758,8302,058,2894,958,896age--meannumericoveralloverall16.65.845.962.359.574.352.449.71.5sdnumericoveralloverall9.85.47.65.67.86.43.83.68.4MedicationsAmoxicilinecountintegeroveralloverall87,07328,18117,32210,96758,62285,07292,15367,56635,059percentagepercentageoveralloverall94.56878483761184.3096942175186.4883093349635676.21109145693487.8384252265095713.350766268558880.969620100222555.938323936425173.3729686122388Ibuprofencountintegeroveralloverall88,13123,77057,86389,79034,44376,08673,11085,24397,582percentagepercentageoveralloverall71.195530286058861.20827866252513.4429233055561866.589078702963965.296727651730245.185843971557951.680410187691567.661079717888.0933094071224 # Example 2 mockSummarisedResult() |>   formatEstimateValue(decimals = c(integer = 0, numeric = 1)) |>   formatHeader(header = c(\"Study strata\", \"strata_name\", \"strata_level\"),               includeHeaderName = FALSE) |>   formatTable(     type = \"gt\",     style = list(\"header\" = list(       gt::cell_fill(color = \"#d9d9d9\"),       gt::cell_text(weight = \"bold\")),       \"header_level\" = list(gt::cell_fill(color = \"#e1e1e1\"),                             gt::cell_text(weight = \"bold\")),       \"column_name\" = list(gt::cell_text(weight = \"bold\")),       \"title\" = list(gt::cell_text(weight = \"bold\"),                      gt::cell_fill(color = \"#c8c8c8\")),       \"group_label\" = gt::cell_fill(color = \"#e1e1e1\")),     na = \"--\",     title = \"gtTable example\",     subtitle = NULL,     caption = NULL,     groupColumn = \"group_level\",     groupAsColumn = FALSE,     groupOrder = c(\"cohort1\", \"cohort2\"),     merge = \"all_columns\"   )     gtTable example                     Study strata            result_id       cdm_name       group_name       variable_name       variable_level       estimate_name       estimate_type       additional_name       additional_level                overall                       age_group &&& sex                       sex                       age_group            overall       <40 &&& Male       >=40 &&& Male       <40 &&& Female       >=40 &&& Female       Male       Female       <40       >=40     cohort1     1 mock cohort_name number subjects -- count integer overall overall 7,312,292 3,986,198 4,305,207 1,454,073 4,511,203 5,787,815 704,171 7,423,262 5,492,207   age -- mean numeric overall overall 77.8 65.8 25.9 91.8 14.9 64.1 20.1 74.4 84.8     sd numeric overall overall 4.4 9.0 7.7 1.3 5.4 1.3 5.1 5.4 2.4   Medications Amoxiciline count integer overall overall 36,924 12,667 73,987 95,587 66,867 46,809 53,819 33,095 62,868     percentage percentage overall overall 6.84064193628728 95.8503520581871 24.4483520975336 92.6283334614709 50.2747076796368 93.5517142061144 43.8799632480368 35.0486536743119 47.6504088379443    Ibuprofen count integer overall overall 13,002 79,191 35,590 96,434 11,868 45,816 52,365 83,706 3,350     percentage percentage overall overall 75.4406645428389 24.2454329272732 62.715786579065 16.8414602987468 44.4789632922038 16.4675234118477 11.8276783032343 36.7464390583336 94.6558905066922cohort2     1 mock cohort_name number subjects -- count integer overall overall 6,345,443 1,366,286 9,302,335 6,511,186 5,287,093 2,251,154 9,832,669 1,090,488 699,455   age -- mean numeric overall overall 85.4 80.3 2.4 79.5 88.7 60.0 43.3 92.0 61.6     sd numeric overall overall 8.0 9.5 4.1 5.1 9.8 3.5 4.6 2.2 0.8   Medications Amoxiciline count integer overall overall 45,255 88,802 78,420 13,806 28,131 70,695 44,219 67,770 70,071     percentage percentage overall overall 96.6159525094554 29.7161926981062 29.0648308349773 85.9722247580066 19.3312666844577 80.9108371380717 36.5486512426287 25.2699653152376 85.6081013800576    Ibuprofen count integer overall overall 4,333 79,210 20,270 6,880 86,444 7,709 43,100 97,362 57,096     percentage percentage overall overall 87.5410763313994 26.0058912448585 65.7298437319696 12.1864625485614 31.8848039023578 62.3061030171812 44.6997430175543 70.8293445874006 89.0028999885544"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/mockSummarisedResult.html","id":null,"dir":"Reference","previous_headings":"","what":"A <summarised_result> object filled with mock data — mockSummarisedResult","title":"A <summarised_result> object filled with mock data — mockSummarisedResult","text":"Creates object class <summarised_result> mock data illustration purposes.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/mockSummarisedResult.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"A <summarised_result> object filled with mock data — mockSummarisedResult","text":"","code":"mockSummarisedResult()"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/mockSummarisedResult.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"A <summarised_result> object filled with mock data — mockSummarisedResult","text":"object class <summarised_result> mock data.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/mockSummarisedResult.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"A <summarised_result> object filled with mock data — mockSummarisedResult","text":"","code":"mockSummarisedResult() #> # A tibble: 126 × 13 #>    result_id cdm_name group_name  group_level strata_name       strata_level    #>        <int> <chr>    <chr>       <chr>       <chr>             <chr>           #>  1         1 mock     cohort_name cohort1     overall           overall         #>  2         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Male    #>  3         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Male   #>  4         1 mock     cohort_name cohort1     age_group &&& sex <40 &&& Female  #>  5         1 mock     cohort_name cohort1     age_group &&& sex >=40 &&& Female #>  6         1 mock     cohort_name cohort1     sex               Male            #>  7         1 mock     cohort_name cohort1     sex               Female          #>  8         1 mock     cohort_name cohort1     age_group         <40             #>  9         1 mock     cohort_name cohort1     age_group         >=40            #> 10         1 mock     cohort_name cohort2     overall           overall         #> # ℹ 116 more rows #> # ℹ 7 more variables: variable_name <chr>, variable_level <chr>, #> #   estimate_name <chr>, estimate_type <chr>, estimate_value <chr>, #> #   additional_name <chr>, additional_level <chr>"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/plotColumns.html","id":null,"dir":"Reference","previous_headings":"","what":"Columns for the plot functions — plotColumns","title":"Columns for the plot functions — plotColumns","text":"Names columns can used input arguments plot functions.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/plotColumns.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Columns for the plot functions — plotColumns","text":"","code":"plotColumns(result)"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/plotColumns.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Columns for the plot functions — plotColumns","text":"result <summarised_result> object.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/plotColumns.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Columns for the plot functions — plotColumns","text":"character vector supported columns plots.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/plotColumns.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Columns for the plot functions — plotColumns","text":"","code":"result <- mockSummarisedResult() plotColumns(result) #>  [1] \"cdm_name\"       \"cohort_name\"    \"age_group\"      \"sex\"            #>  [5] \"variable_name\"  \"variable_level\" \"count\"          \"mean\"           #>  [9] \"sd\"             \"percentage\""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/reexports.html","id":null,"dir":"Reference","previous_headings":"","what":"Objects exported from other packages — reexports","title":"Objects exported from other packages — reexports","text":"objects imported packages. Follow links see documentation. generics tidy omopgenerics additionalColumns, addSettings, bind, exportSummarisedResult, filterAdditional, filterGroup, filterSettings, filterStrata, groupColumns, importSummarisedResult, pivotEstimates, settings, settingsColumns, splitAdditional, splitAll, splitGroup, splitStrata, strataColumns, suppress, tidy, tidyColumns, uniteAdditional, uniteGroup, uniteStrata","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/scatterPlot.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a scatter plot visualisation from a <summarised_result> object — scatterPlot","title":"Create a scatter plot visualisation from a <summarised_result> object — scatterPlot","text":"Create scatter plot visualisation <summarised_result> object","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/scatterPlot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a scatter plot visualisation from a <summarised_result> object — scatterPlot","text":"","code":"scatterPlot(   result,   x,   y,   line,   point,   ribbon,   ymin = NULL,   ymax = NULL,   facet = NULL,   colour = NULL,   group = colour,   label = character() )"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/scatterPlot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a scatter plot visualisation from a <summarised_result> object — scatterPlot","text":"result <summarised_result> object. x Column estimate name used x variable. y Column estimate name used y variable line Whether plot line using geom_line. point Whether plot points using geom_point. ribbon Whether plot ribbon using geom_ribbon. ymin Lower limit error bars, provided plot using geom_errorbar. ymax Upper limit error bars, provided plot using geom_errorbar. facet Variables facet , formula can provided specify variables used rows ones columns. colour Columns use determine colors. group Columns use determine group. label Character vector columns display interactively plotly.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/scatterPlot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a scatter plot visualisation from a <summarised_result> object — scatterPlot","text":"plot object.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/scatterPlot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a scatter plot visualisation from a <summarised_result> object — scatterPlot","text":"","code":"result <- mockSummarisedResult() |>   dplyr::filter(variable_name == \"age\")  scatterPlot(   result = result,   x = \"cohort_name\",   y = \"mean\",   line = TRUE,   point = TRUE,   ribbon = FALSE,   facet = age_group ~ sex) #> `geom_line()`: Each group consists of only one observation. #> ℹ Do you need to adjust the group aesthetic? #> `geom_line()`: Each group consists of only one observation. #> ℹ Do you need to adjust the group aesthetic? #> `geom_line()`: Each group consists of only one observation. #> ℹ Do you need to adjust the group aesthetic? #> `geom_line()`: Each group consists of only one observation. #> ℹ Do you need to adjust the group aesthetic? #> `geom_line()`: Each group consists of only one observation. #> ℹ Do you need to adjust the group aesthetic? #> `geom_line()`: Each group consists of only one observation. #> ℹ Do you need to adjust the group aesthetic? #> `geom_line()`: Each group consists of only one observation. #> ℹ Do you need to adjust the group aesthetic? #> `geom_line()`: Each group consists of only one observation. #> ℹ Do you need to adjust the group aesthetic? #> `geom_line()`: Each group consists of only one observation. #> ℹ Do you need to adjust the group aesthetic?"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableColumns.html","id":null,"dir":"Reference","previous_headings":"","what":"Columns for the table functions — tableColumns","title":"Columns for the table functions — tableColumns","text":"Names columns can used input arguments table functions.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableColumns.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Columns for the table functions — tableColumns","text":"","code":"tableColumns(result)"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableColumns.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Columns for the table functions — tableColumns","text":"result <summarised_result> object.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableColumns.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Columns for the table functions — tableColumns","text":"character vector supported columns tables.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableColumns.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Columns for the table functions — tableColumns","text":"","code":"result <- mockSummarisedResult() tableColumns(result) #> [1] \"cdm_name\"       \"cohort_name\"    \"age_group\"      \"sex\"            #> [5] \"variable_name\"  \"variable_level\" \"estimate_name\""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableOptions.html","id":null,"dir":"Reference","previous_headings":"","what":"Additional table formatting options for visOmopTable() and visTable() — tableOptions","title":"Additional table formatting options for visOmopTable() and visTable() — tableOptions","text":"function provides list allowed inputs .option argument visOmopTable() visTable(), corresponding default values.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableOptions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Additional table formatting options for visOmopTable() and visTable() — tableOptions","text":"","code":"tableOptions()"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableOptions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Additional table formatting options for visOmopTable() and visTable() — tableOptions","text":"named list default options table customisation.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableOptions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Additional table formatting options for visOmopTable() and visTable() — tableOptions","text":"","code":"tableOptions() #> $decimals #>    integer percentage    numeric proportion  #>          0          2          2          2  #>  #> $decimalMark #> [1] \".\" #>  #> $bigMark #> [1] \",\" #>  #> $keepNotFormatted #> [1] TRUE #>  #> $useFormatOrder #> [1] TRUE #>  #> $delim #> [1] \"\\n\" #>  #> $includeHeaderName #> [1] TRUE #>  #> $includeHeaderKey #> [1] TRUE #>  #> $style #> [1] \"default\" #>  #> $na #> [1] \"-\" #>  #> $title #> NULL #>  #> $subtitle #> NULL #>  #> $caption #> NULL #>  #> $groupAsColumn #> [1] FALSE #>  #> $groupOrder #> NULL #>  #> $merge #> [1] \"all_columns\" #>"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableStyle.html","id":null,"dir":"Reference","previous_headings":"","what":"Supported predefined styles for formatted tables — tableStyle","title":"Supported predefined styles for formatted tables — tableStyle","text":"Supported predefined styles formatted tables","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableStyle.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Supported predefined styles for formatted tables — tableStyle","text":"","code":"tableStyle(type = \"gt\")"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableStyle.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Supported predefined styles for formatted tables — tableStyle","text":"type Character string specifying formatted table class. See tableType() supported classes. Default \"gt\".","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableStyle.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Supported predefined styles for formatted tables — tableStyle","text":"code expression selected style table type.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableStyle.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Supported predefined styles for formatted tables — tableStyle","text":"","code":"tableStyle(\"gt\") #> list(header = list(gt::cell_fill(color = \"#c8c8c8\"), gt::cell_text(weight = \"bold\",  #>     align = \"center\")), header_name = list(gt::cell_fill(color = \"#d9d9d9\"),  #>     gt::cell_text(weight = \"bold\", align = \"center\")), header_level = list(gt::cell_fill(color = \"#e1e1e1\"),  #>     gt::cell_text(weight = \"bold\", align = \"center\")), column_name = list(gt::cell_text(weight = \"bold\",  #>     align = \"center\")), group_label = list(gt::cell_fill(color = \"#e9e9e9\"),  #>     gt::cell_text(weight = \"bold\")), title = list(gt::cell_text(weight = \"bold\",  #>     size = 15, align = \"center\")), subtitle = list(gt::cell_text(weight = \"bold\",  #>     size = 12, align = \"center\")), body = list()) tableStyle(\"flextable\") #> list(header = list(cell = officer::fp_cell(background.color = \"#c8c8c8\"),  #>     text = officer::fp_text(bold = TRUE)), header_name = list(cell = officer::fp_cell(background.color = \"#d9d9d9\"),  #>     text = officer::fp_text(bold = TRUE)), header_level = list(cell = officer::fp_cell(background.color = \"#e1e1e1\"),  #>     text = officer::fp_text(bold = TRUE)), column_name = list(text = officer::fp_text(bold = TRUE)),  #>     group_label = list(cell = officer::fp_cell(background.color = \"#e9e9e9\",  #>         border = officer::fp_border(color = \"gray\")), text = officer::fp_text(bold = TRUE)),  #>     title = list(text = officer::fp_text(bold = TRUE, font.size = 15)),  #>     subtitle = list(text = officer::fp_text(bold = TRUE, font.size = 12)),  #>     body = list())"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableType.html","id":null,"dir":"Reference","previous_headings":"","what":"Supported table classes — tableType","title":"Supported table classes — tableType","text":"function returns supported table classes can used type argument visOmopTable(), visTable(), formatTable() functions.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableType.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Supported table classes — tableType","text":"","code":"tableType()"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableType.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Supported table classes — tableType","text":"character vector supported table types.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/tableType.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Supported table classes — tableType","text":"","code":"tableType() #> [1] \"gt\"        \"flextable\" \"tibble\"    \"datatable\""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/themeVisOmop.html","id":null,"dir":"Reference","previous_headings":"","what":"Apply visOmopResults default styling to a ggplot — themeVisOmop","title":"Apply visOmopResults default styling to a ggplot — themeVisOmop","text":"Apply visOmopResults default styling ggplot","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/themeVisOmop.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Apply visOmopResults default styling to a ggplot — themeVisOmop","text":"","code":"themeVisOmop(fontsizeRef = 10)"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/themeVisOmop.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Apply visOmopResults default styling to a ggplot — themeVisOmop","text":"fontsizeRef integer use reference adjusting label fontsize.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/themeVisOmop.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Apply visOmopResults default styling to a ggplot — themeVisOmop","text":"","code":"result <- mockSummarisedResult() |> dplyr::filter(variable_name == \"age\")  barPlot(   result = result,   x = \"cohort_name\",   y = \"mean\",   facet = c(\"age_group\", \"sex\"),   colour = \"sex\") +   themeVisOmop()"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visOmopResults-package.html","id":null,"dir":"Reference","previous_headings":"","what":"visOmopResults: Graphs and Tables for OMOP Results — visOmopResults-package","title":"visOmopResults: Graphs and Tables for OMOP Results — visOmopResults-package","text":"Provides methods transform omop_result objects formatted tables figures, facilitating visualisation study results working Observational Medical Outcomes Partnership (OMOP) Common Data Model.","code":""},{"path":[]},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visOmopResults-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"visOmopResults: Graphs and Tables for OMOP Results — visOmopResults-package","text":"Maintainer: N<U+00FA>ria Mercad<U+00E9>-Besora nuria.mercadebesora@ndorms.ox.ac.uk (ORCID) Authors: Mart<U+00ED> Catal<U+00E0> marti.catalasabate@ndorms.ox.ac.uk (ORCID) contributors: Yuchen Guo yuchen.guo@ndorms.ox.ac.uk (ORCID) [contributor] Elin Rowlands elin.rowlands@ndorms.ox.ac.uk (ORCID) [contributor] Edward Burn edward.burn@ndorms.ox.ac.uk (ORCID) [contributor]","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visOmopTable.html","id":null,"dir":"Reference","previous_headings":"","what":"Format a <summarised_result> object into a gt, flextable, or tibble object — visOmopTable","title":"Format a <summarised_result> object into a gt, flextable, or tibble object — visOmopTable","text":"function combines functionalities formatEstimateValue(), estimateName(), formatHeader(), formatTable() single function specifically <summarised_result> objects.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visOmopTable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format a <summarised_result> object into a gt, flextable, or tibble object — visOmopTable","text":"","code":"visOmopTable(   result,   estimateName = character(),   header = character(),   settingsColumn = character(),   groupColumn = character(),   rename = character(),   type = \"gt\",   hide = character(),   columnOrder = character(),   factor = list(),   showMinCellCount = TRUE,   .options = list() )"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visOmopTable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format a <summarised_result> object into a gt, flextable, or tibble object — visOmopTable","text":"result <summarised_result> object. estimateName named list estimate names join, sorted computation order. Use <...> indicate estimate names. header vector specifying elements include header. order elements matters, first topmost header. Elements header can : columns returned tableColumns(result) create header columns. input create overall header. settingsColumn character vector names settings include table. see options use settingsColumns(result). groupColumn Columns use group labels, see options use tableColumns(result). default, name new group tidy* column names separated \";\". specify custom group name, use named list : list(\"newGroupName\" = c(\"variable_name\", \"variable_level\")). *tidy: tidy format applied column names replaces \"_\" space converts sentence case. Use rename customise specific column names. rename named vector customise column names, e.g., c(\"Database name\" = \"cdm_name\"). function renames column names specified tidy* format. type desired format output table. See tableType() allowed options. hide Columns drop output table. default, result_id estimate_type always dropped. columnOrder Character vector establishing position columns formatted table. Columns either header, groupColumn, hide ignored. factor named list names refer columns (see available columns tableColumns()) list elements level order column arrange results. column order list used arranging result. showMinCellCount TRUE, suppressed estimates indicated \"<{min_cell_count}\", otherwise, default na defined .options used. .options named list additional formatting options. visOmopResults::tableOptions() shows allowed arguments default values.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visOmopTable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format a <summarised_result> object into a gt, flextable, or tibble object — visOmopTable","text":"tibble, gt, flextable object.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visOmopTable.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format a <summarised_result> object into a gt, flextable, or tibble object — visOmopTable","text":"","code":"result <- mockSummarisedResult() result |>   visOmopTable(     estimateName = c(\"N%\" = \"<count> (<percentage>)\",                      \"N\" = \"<count>\",                      \"Mean (SD)\" = \"<mean> (<sd>)\"),     header = c(\"group\"),     rename = c(\"Database name\" = \"cdm_name\"),     groupColumn = strataColumns(result)   )     Database name       Variable name       Variable level       Estimate name                Cohort name            cohort1       cohort2     overall; overall     mock number subjects - N 2,009,283 3,012,543 age - Mean (SD) 27.92 (5.88) 33.71 (6.72) Medications Amoxiciline N% 82,683 (49.14) 20,832 (29.82)  Ibuprofen N% 90,252 (24.88) 54,539 (58.02)<40; Male     mock number subjects - N 8,141,156 7,204,667 age - Mean (SD) 67.27 (4.92) 14.12 (8.20) Medications Amoxiciline N% 61,938 (84.54) 22,826 (38.13)  Ibuprofen N% 43,803 (74.80) 72,510 (38.57)>=40; Male     mock number subjects - N 6,537,801 2,614,054 age - Mean (SD) 6.01 (2.86) 35.26 (9.15) Medications Amoxiciline N% 84,105 (2.51) 5,044 (24.78)  Ibuprofen N% 80,676 (40.72) 52,548 (23.65)<40; Female     mock number subjects - N 3,532,520 1,076,963 age - Mean (SD) 98.85 (0.08) 40.14 (6.90) Medications Amoxiciline N% 42,725 (54.84) 56,182 (34.50)  Ibuprofen N% 48,150 (56.17) 61,894 (51.95)>=40; Female     mock number subjects - N 5,965,949 2,624,227 age - Mean (SD) 28.23 (5.51) 88.89 (4.92) Medications Amoxiciline N% 76,929 (95.55) 69,425 (41.98)  Ibuprofen N% 25,804 (75.05) 17,896 (64.12)overall; Male     mock number subjects - N 7,277,044 1,867,062 age - Mean (SD) 55.41 (8.13) 31.26 (6.47) Medications Amoxiciline N% 71,214 (14.05) 22,794 (65.91)  Ibuprofen N% 17,014 (55.12) 76,772 (82.99)overall; Female     mock number subjects - N 9,955,685 5,424,417 age - Mean (SD) 89.01 (6.44) 6.17 (4.57) Medications Amoxiciline N% 6,337 (71.03) 96,031 (95.40)  Ibuprofen N% 16,061 (47.33) 81,629 (91.91)<40; overall     mock number subjects - N 4,980,553 655,185 age - Mean (SD) 2.28 (0.69) 67.95 (1.25) Medications Amoxiciline N% 42,601 (12.64) 49,284 (46.99)  Ibuprofen N% 66,139 (6.26) 19,458 (92.94)>=40; overall     mock number subjects - N 2,302,948 8,803,851 age - Mean (SD) 67.77 (7.29) 37.82 (6.04) Medications Amoxiciline N% 8,828 (83.57) 72,321 (15.06)  Ibuprofen N% 46,855 (9.39) 21,251 (64.53)"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visTable.html","id":null,"dir":"Reference","previous_headings":"","what":"Generate a formatted table from a <data.table> — visTable","title":"Generate a formatted table from a <data.table> — visTable","text":"function combines functionalities formatEstimateValue(), formatEstimateName(), formatHeader(), formatTable() single function. require input table <summarised_result>, expect specific fields apply formatting functionalities.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visTable.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Generate a formatted table from a <data.table> — visTable","text":"","code":"visTable(   result,   estimateName = character(),   header = character(),   groupColumn = character(),   rename = character(),   type = \"gt\",   hide = character(),   .options = list() )"},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visTable.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Generate a formatted table from a <data.table> — visTable","text":"result table format. estimateName named list estimate names join, sorted computation order. Use <...> indicate estimate names. argument requires table estimate_name estimate_value columns. header vector specifying elements include header. order elements matters, first topmost header. vector elements can column names labels overall headers. table must contain estimate_value column pivot headers. groupColumn Columns use group labels. default, name new group tidy* column names separated \";\". specify custom group name, use named list : list(\"newGroupName\" = c(\"variable_name\", \"variable_level\")). *tidy: tidy format applied column names replaces \"_\" space converts sentence case. Use rename customise specific column names. rename named vector customise column names, e.g., c(\"Database name\" = \"cdm_name\"). function rename column names specified tidy* format. type desired format output table. See tableType() allowed options. hide Columns drop output table. .options named list additional formatting options. visOmopResults::tableOptions() shows allowed arguments default values.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visTable.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Generate a formatted table from a <data.table> — visTable","text":"tibble, gt, flextable object.","code":""},{"path":"https://darwin-eu.github.io/visOmopResults/reference/visTable.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Generate a formatted table from a <data.table> — visTable","text":"","code":"result <- mockSummarisedResult() result |>   visTable(     estimateName = c(\"N%\" = \"<count> (<percentage>)\",                      \"N\" = \"<count>\",                      \"Mean (SD)\" = \"<mean> (<sd>)\"),     header = c(\"Estimate\"),     rename = c(\"Database name\" = \"cdm_name\"),     groupColumn = c(\"strata_name\", \"strata_level\"),     hide = c(\"additional_name\", \"additional_level\", \"estimate_type\", \"result_type\")   )     Result id       Database name       Group name       Group level       Variable name       Variable level       Estimate name       Estimate     overall; overall     1 mock cohort_name cohort1 number subjects - N 2,202,471   cohort2 number subjects - N 4,513,757   cohort1 age - Mean (SD) 44.81 (7.83)   cohort2 age - Mean (SD) 26.89 (7.36)   cohort1 Medications Amoxiciline N% 62,237 (92.84)   cohort2 Medications Amoxiciline N% 33,863 (63.98)   cohort1 Medications Ibuprofen N% 24,332 (61.44)   cohort2 Medications Ibuprofen N% 16,482 (1.81)age_group &&& sex; <40 &&& Male     1 mock cohort_name cohort1 number subjects - N 371,822   cohort2 number subjects - N 7,942,700   cohort1 age - Mean (SD) 82.39 (6.22)   cohort2 age - Mean (SD) 88.35 (9.41)   cohort1 Medications Amoxiciline N% 55,533 (41.34)   cohort2 Medications Amoxiciline N% 76,968 (88.25)   cohort1 Medications Ibuprofen N% 51,505 (19.24)   cohort2 Medications Ibuprofen N% 18,098 (38.20)age_group &&& sex; >=40 &&& Male     1 mock cohort_name cohort1 number subjects - N 6,980,541   cohort2 number subjects - N 8,246,223   cohort1 age - Mean (SD) 96.94 (8.66)   cohort2 age - Mean (SD) 67.06 (8.61)   cohort1 Medications Amoxiciline N% 96,107 (13.10)   cohort2 Medications Amoxiciline N% 30,134 (94.62)   cohort1 Medications Ibuprofen N% 86,319 (7.18)   cohort2 Medications Ibuprofen N% 99,645 (51.36)age_group &&& sex; <40 &&& Female     1 mock cohort_name cohort1 number subjects - N 1,498,340   cohort2 number subjects - N 2,090,516   cohort1 age - Mean (SD) 29.54 (9.20)   cohort2 age - Mean (SD) 7.43 (3.64)   cohort1 Medications Amoxiciline N% 91,564 (6.12)   cohort2 Medications Amoxiciline N% 62,964 (70.94)   cohort1 Medications Ibuprofen N% 4,056 (30.62)   cohort2 Medications Ibuprofen N% 64,511 (4.72)age_group &&& sex; >=40 &&& Female     1 mock cohort_name cohort1 number subjects - N 5,424,376   cohort2 number subjects - N 1,682,065   cohort1 age - Mean (SD) 23.27 (3.25)   cohort2 age - Mean (SD) 68.53 (9.13)   cohort1 Medications Amoxiciline N% 60,328 (88.61)   cohort2 Medications Amoxiciline N% 80,250 (92.36)   cohort1 Medications Ibuprofen N% 46,003 (17.46)   cohort2 Medications Ibuprofen N% 91,810 (80.31)sex; Male     1 mock cohort_name cohort1 number subjects - N 7,967,724   cohort2 number subjects - N 9,802,742   cohort1 age - Mean (SD) 32.55 (9.16)   cohort2 age - Mean (SD) 60.08 (7.53)   cohort1 Medications Amoxiciline N% 31,155 (59.22)   cohort2 Medications Amoxiciline N% 54,224 (1.62)   cohort1 Medications Ibuprofen N% 16,600 (88.78)   cohort2 Medications Ibuprofen N% 79,507 (63.41)sex; Female     1 mock cohort_name cohort1 number subjects - N 7,196,247   cohort2 number subjects - N 6,006,700   cohort1 age - Mean (SD) 10.04 (0.81)   cohort2 age - Mean (SD) 70.61 (6.41)   cohort1 Medications Amoxiciline N% 55,515 (72.24)   cohort2 Medications Amoxiciline N% 63,100 (17.15)   cohort1 Medications Ibuprofen N% 91,538 (49.78)   cohort2 Medications Ibuprofen N% 91,310 (77.13)age_group; <40     1 mock cohort_name cohort1 number subjects - N 7,281,897   cohort2 number subjects - N 1,516,763   cohort1 age - Mean (SD) 33.02 (8.56)   cohort2 age - Mean (SD) 46.82 (7.95)   cohort1 Medications Amoxiciline N% 93,760 (51.24)   cohort2 Medications Amoxiciline N% 18,979 (21.40)   cohort1 Medications Ibuprofen N% 40,942 (69.39)   cohort2 Medications Ibuprofen N% 39,056 (50.18)age_group; >=40     1 mock cohort_name cohort1 number subjects - N 478,162   cohort2 number subjects - N 2,927,387   cohort1 age - Mean (SD) 19.26 (3.05)   cohort2 age - Mean (SD) 1.10 (9.85)   cohort1 Medications Amoxiciline N% 36,504 (29.61)   cohort2 Medications Amoxiciline N% 20,345 (84.51)   cohort1 Medications Ibuprofen N% 64,053 (87.42)   cohort2 Medications Ibuprofen N% 35,740 (71.13)"},{"path":"https://darwin-eu.github.io/visOmopResults/news/index.html","id":"visomopresults-100","dir":"Changelog","previous_headings":"","what":"visOmopResults 1.0.0","title":"visOmopResults 1.0.0","text":"Added NEWS.md file track changes package.","code":""}]
diff --git a/sitemap.xml b/sitemap.xml
index acf8538..d74f413 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -1,14 +1,16 @@
 <urlset xmlns = 'http://www.sitemaps.org/schemas/sitemap/0.9'>
 <url><loc>https://darwin-eu.github.io/visOmopResults/404.html</loc></url>
 <url><loc>https://darwin-eu.github.io/visOmopResults/LICENSE.html</loc></url>
+<url><loc>https://darwin-eu.github.io/visOmopResults/articles/a01_tables.html</loc></url>
+<url><loc>https://darwin-eu.github.io/visOmopResults/articles/a02_plots.html</loc></url>
 <url><loc>https://darwin-eu.github.io/visOmopResults/articles/index.html</loc></url>
-<url><loc>https://darwin-eu.github.io/visOmopResults/articles/plots.html</loc></url>
-<url><loc>https://darwin-eu.github.io/visOmopResults/articles/tables.html</loc></url>
 <url><loc>https://darwin-eu.github.io/visOmopResults/authors.html</loc></url>
 <url><loc>https://darwin-eu.github.io/visOmopResults/index.html</loc></url>
+<url><loc>https://darwin-eu.github.io/visOmopResults/news/index.html</loc></url>
 <url><loc>https://darwin-eu.github.io/visOmopResults/reference/barPlot.html</loc></url>
 <url><loc>https://darwin-eu.github.io/visOmopResults/reference/boxPlot.html</loc></url>
 <url><loc>https://darwin-eu.github.io/visOmopResults/reference/customiseText.html</loc></url>
+<url><loc>https://darwin-eu.github.io/visOmopResults/reference/emptyPlot.html</loc></url>
 <url><loc>https://darwin-eu.github.io/visOmopResults/reference/emptyTable.html</loc></url>
 <url><loc>https://darwin-eu.github.io/visOmopResults/reference/formatEstimateName.html</loc></url>
 <url><loc>https://darwin-eu.github.io/visOmopResults/reference/formatEstimateValue.html</loc></url>