diff --git a/main/404.html b/main/404.html
index 81efa2d4e..21ebfd0bf 100644
--- a/main/404.html
+++ b/main/404.html
@@ -32,7 +32,7 @@
     
     <a class="navbar-brand me-2" href="https://insightsengineering.github.io/cardx/index.html">cardx</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
     <div style="width: 140px; margin-left: 0.5rem;"> <small class="nav-text text-muted me-auto">part of</small> <img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/nest.png?raw=true" alt="NEST" style="height: 30px;"><a href="https://pharmaverse.org/" class="external-link"><img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/pharmaverse.png?raw=true" alt="pharmaverse" style="height: 28px;"></a> </div>
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -47,14 +47,6 @@
 <li class="nav-item">
   <a class="nav-link" href="https://insightsengineering.github.io/cardx/news/index.html">Changelog</a>
 </li>
-<!-- start dropdown for versions --> <li class="nav-item dropdown">
-        <a href="#" class="nav-link dropdown-toggle"
-          data-bs-toggle="dropdown" role="button"
-          aria-expanded="false" aria-haspopup="true"
-          id="dropdown-versions">Versions</a> <div class="dropdown-menu" aria-labelledby="dropdown-versions"> <a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/main">main</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/latest-tag">latest-tag</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/v0.1.0">v0.1.0</a> </div></li>
-<!-- end dropdown for versions -->
       </ul>
 <form class="form-inline my-2 my-lg-0" role="search">
         <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="search.json" id="search-input" placeholder="Search for" autocomplete="off">
diff --git a/main/CODE_OF_CONDUCT.html b/main/CODE_OF_CONDUCT.html
index 5af37de8d..ccab42883 100644
--- a/main/CODE_OF_CONDUCT.html
+++ b/main/CODE_OF_CONDUCT.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="index.html">cardx</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
     <div style="width: 140px; margin-left: 0.5rem;"> <small class="nav-text text-muted me-auto">part of</small> <img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/nest.png?raw=true" alt="NEST" style="height: 30px;"><a href="https://pharmaverse.org/" class="external-link"><img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/pharmaverse.png?raw=true" alt="pharmaverse" style="height: 28px;"></a> </div>
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -24,14 +24,6 @@
 <li class="nav-item">
   <a class="nav-link" href="news/index.html">Changelog</a>
 </li>
-<!-- start dropdown for versions --> <li class="nav-item dropdown">
-        <a href="#" class="nav-link dropdown-toggle"
-          data-bs-toggle="dropdown" role="button"
-          aria-expanded="false" aria-haspopup="true"
-          id="dropdown-versions">Versions</a> <div class="dropdown-menu" aria-labelledby="dropdown-versions"> <a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/main">main</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/latest-tag">latest-tag</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/v0.1.0">v0.1.0</a> </div></li>
-<!-- end dropdown for versions -->
       </ul><form class="form-inline my-2 my-lg-0" role="search">
         <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
 
diff --git a/main/CONTRIBUTING.html b/main/CONTRIBUTING.html
index 5d587ce9d..2a5cf2bb3 100644
--- a/main/CONTRIBUTING.html
+++ b/main/CONTRIBUTING.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="index.html">cardx</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
     <div style="width: 140px; margin-left: 0.5rem;"> <small class="nav-text text-muted me-auto">part of</small> <img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/nest.png?raw=true" alt="NEST" style="height: 30px;"><a href="https://pharmaverse.org/" class="external-link"><img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/pharmaverse.png?raw=true" alt="pharmaverse" style="height: 28px;"></a> </div>
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -24,14 +24,6 @@
 <li class="nav-item">
   <a class="nav-link" href="news/index.html">Changelog</a>
 </li>
-<!-- start dropdown for versions --> <li class="nav-item dropdown">
-        <a href="#" class="nav-link dropdown-toggle"
-          data-bs-toggle="dropdown" role="button"
-          aria-expanded="false" aria-haspopup="true"
-          id="dropdown-versions">Versions</a> <div class="dropdown-menu" aria-labelledby="dropdown-versions"> <a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/main">main</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/latest-tag">latest-tag</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/v0.1.0">v0.1.0</a> </div></li>
-<!-- end dropdown for versions -->
       </ul><form class="form-inline my-2 my-lg-0" role="search">
         <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
 
diff --git a/main/LICENSE-text.html b/main/LICENSE-text.html
index 9c88a27bd..540fa818f 100644
--- a/main/LICENSE-text.html
+++ b/main/LICENSE-text.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="index.html">cardx</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
     <div style="width: 140px; margin-left: 0.5rem;"> <small class="nav-text text-muted me-auto">part of</small> <img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/nest.png?raw=true" alt="NEST" style="height: 30px;"><a href="https://pharmaverse.org/" class="external-link"><img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/pharmaverse.png?raw=true" alt="pharmaverse" style="height: 28px;"></a> </div>
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -24,14 +24,6 @@
 <li class="nav-item">
   <a class="nav-link" href="news/index.html">Changelog</a>
 </li>
-<!-- start dropdown for versions --> <li class="nav-item dropdown">
-        <a href="#" class="nav-link dropdown-toggle"
-          data-bs-toggle="dropdown" role="button"
-          aria-expanded="false" aria-haspopup="true"
-          id="dropdown-versions">Versions</a> <div class="dropdown-menu" aria-labelledby="dropdown-versions"> <a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/main">main</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/latest-tag">latest-tag</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/v0.1.0">v0.1.0</a> </div></li>
-<!-- end dropdown for versions -->
       </ul><form class="form-inline my-2 my-lg-0" role="search">
         <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
 
diff --git a/main/PULL_REQUEST_TEMPLATE.html b/main/PULL_REQUEST_TEMPLATE.html
index 43636f2a9..85a46962a 100644
--- a/main/PULL_REQUEST_TEMPLATE.html
+++ b/main/PULL_REQUEST_TEMPLATE.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="index.html">cardx</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
     <div style="width: 140px; margin-left: 0.5rem;"> <small class="nav-text text-muted me-auto">part of</small> <img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/nest.png?raw=true" alt="NEST" style="height: 30px;"><a href="https://pharmaverse.org/" class="external-link"><img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/pharmaverse.png?raw=true" alt="pharmaverse" style="height: 28px;"></a> </div>
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -24,14 +24,6 @@
 <li class="nav-item">
   <a class="nav-link" href="news/index.html">Changelog</a>
 </li>
-<!-- start dropdown for versions --> <li class="nav-item dropdown">
-        <a href="#" class="nav-link dropdown-toggle"
-          data-bs-toggle="dropdown" role="button"
-          aria-expanded="false" aria-haspopup="true"
-          id="dropdown-versions">Versions</a> <div class="dropdown-menu" aria-labelledby="dropdown-versions"> <a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/main">main</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/latest-tag">latest-tag</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/v0.1.0">v0.1.0</a> </div></li>
-<!-- end dropdown for versions -->
       </ul><form class="form-inline my-2 my-lg-0" role="search">
         <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
 
diff --git a/main/SECURITY.html b/main/SECURITY.html
index 4ff4d7976..8d0dc04f9 100644
--- a/main/SECURITY.html
+++ b/main/SECURITY.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="index.html">cardx</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
     <div style="width: 140px; margin-left: 0.5rem;"> <small class="nav-text text-muted me-auto">part of</small> <img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/nest.png?raw=true" alt="NEST" style="height: 30px;"><a href="https://pharmaverse.org/" class="external-link"><img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/pharmaverse.png?raw=true" alt="pharmaverse" style="height: 28px;"></a> </div>
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -24,14 +24,6 @@
 <li class="nav-item">
   <a class="nav-link" href="news/index.html">Changelog</a>
 </li>
-<!-- start dropdown for versions --> <li class="nav-item dropdown">
-        <a href="#" class="nav-link dropdown-toggle"
-          data-bs-toggle="dropdown" role="button"
-          aria-expanded="false" aria-haspopup="true"
-          id="dropdown-versions">Versions</a> <div class="dropdown-menu" aria-labelledby="dropdown-versions"> <a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/main">main</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/latest-tag">latest-tag</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/v0.1.0">v0.1.0</a> </div></li>
-<!-- end dropdown for versions -->
       </ul><form class="form-inline my-2 my-lg-0" role="search">
         <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
 
diff --git a/main/authors.html b/main/authors.html
index 3a127a12a..7e16115cf 100644
--- a/main/authors.html
+++ b/main/authors.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="index.html">cardx</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
     <div style="width: 140px; margin-left: 0.5rem;"> <small class="nav-text text-muted me-auto">part of</small> <img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/nest.png?raw=true" alt="NEST" style="height: 30px;"><a href="https://pharmaverse.org/" class="external-link"><img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/pharmaverse.png?raw=true" alt="pharmaverse" style="height: 28px;"></a> </div>
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -24,14 +24,6 @@
 <li class="nav-item">
   <a class="nav-link" href="news/index.html">Changelog</a>
 </li>
-<!-- start dropdown for versions --> <li class="nav-item dropdown">
-        <a href="#" class="nav-link dropdown-toggle"
-          data-bs-toggle="dropdown" role="button"
-          aria-expanded="false" aria-haspopup="true"
-          id="dropdown-versions">Versions</a> <div class="dropdown-menu" aria-labelledby="dropdown-versions"> <a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/main">main</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/latest-tag">latest-tag</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/v0.1.0">v0.1.0</a> </div></li>
-<!-- end dropdown for versions -->
       </ul><form class="form-inline my-2 my-lg-0" role="search">
         <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
 
@@ -78,13 +70,13 @@ <h2 id="citation">Citation</h2>
 
       <p>Sjoberg D, Yogasekaram A, de la Rua E (2024).
 <em>cardx: Extra Analysis Results Data Utilities</em>.
-R package version 0.1.0.9025, <a href="https://github.com/insightsengineering/cardx" class="external-link">https://github.com/insightsengineering/cardx</a>. 
+R package version 0.1.0.9026, <a href="https://github.com/insightsengineering/cardx" class="external-link">https://github.com/insightsengineering/cardx</a>. 
 </p>
       <pre>@Manual{,
   title = {cardx: Extra Analysis Results Data Utilities},
   author = {Daniel Sjoberg and Abinaya Yogasekaram and Emily {de la Rua}},
   year = {2024},
-  note = {R package version 0.1.0.9025},
+  note = {R package version 0.1.0.9026},
   url = {https://github.com/insightsengineering/cardx},
 }</pre>
     </div>
diff --git a/main/index.html b/main/index.html
index 5db2af257..ed0e3665b 100644
--- a/main/index.html
+++ b/main/index.html
@@ -34,7 +34,7 @@
     
     <a class="navbar-brand me-2" href="index.html">cardx</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
     <div style="width: 140px; margin-left: 0.5rem;"> <small class="nav-text text-muted me-auto">part of</small> <img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/nest.png?raw=true" alt="NEST" style="height: 30px;"><a href="https://pharmaverse.org/" class="external-link"><img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/pharmaverse.png?raw=true" alt="pharmaverse" style="height: 28px;"></a> </div>
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -49,14 +49,6 @@
 <li class="nav-item">
   <a class="nav-link" href="news/index.html">Changelog</a>
 </li>
-<!-- start dropdown for versions --> <li class="nav-item dropdown">
-        <a href="#" class="nav-link dropdown-toggle"
-          data-bs-toggle="dropdown" role="button"
-          aria-expanded="false" aria-haspopup="true"
-          id="dropdown-versions">Versions</a> <div class="dropdown-menu" aria-labelledby="dropdown-versions"> <a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/main">main</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/latest-tag">latest-tag</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/v0.1.0">v0.1.0</a> </div></li>
-<!-- end dropdown for versions -->
       </ul>
 <form class="form-inline my-2 my-lg-0" role="search">
         <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="search.json" id="search-input" placeholder="Search for" autocomplete="off">
diff --git a/main/news/index.html b/main/news/index.html
index 3160eb319..91e3fc4f5 100644
--- a/main/news/index.html
+++ b/main/news/index.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cardx</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
     <div style="width: 140px; margin-left: 0.5rem;"> <small class="nav-text text-muted me-auto">part of</small> <img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/nest.png?raw=true" alt="NEST" style="height: 30px;"><a href="https://pharmaverse.org/" class="external-link"><img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/pharmaverse.png?raw=true" alt="pharmaverse" style="height: 28px;"></a> </div>
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -24,14 +24,6 @@
 <li class="active nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-<!-- start dropdown for versions --> <li class="nav-item dropdown">
-        <a href="#" class="nav-link dropdown-toggle"
-          data-bs-toggle="dropdown" role="button"
-          aria-expanded="false" aria-haspopup="true"
-          id="dropdown-versions">Versions</a> <div class="dropdown-menu" aria-labelledby="dropdown-versions"> <a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/main">main</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/latest-tag">latest-tag</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/v0.1.0">v0.1.0</a> </div></li>
-<!-- end dropdown for versions -->
       </ul><form class="form-inline my-2 my-lg-0" role="search">
         <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
 
@@ -53,9 +45,9 @@
     </div>
 
     <div class="section level2">
-<h2 class="pkg-version" data-toc-text="0.1.0.9025" id="cardx-0109025">cardx 0.1.0.9025<a class="anchor" aria-label="anchor" href="#cardx-0109025"></a></h2>
+<h2 class="pkg-version" data-toc-text="0.1.0.9026" id="cardx-0109026">cardx 0.1.0.9026<a class="anchor" aria-label="anchor" href="#cardx-0109026"></a></h2>
 <div class="section level4">
-<h4 id="breaking-changes-0-1-0-9025">Breaking Changes<a class="anchor" aria-label="anchor" href="#breaking-changes-0-1-0-9025"></a></h4>
+<h4 id="breaking-changes-0-1-0-9026">Breaking Changes<a class="anchor" aria-label="anchor" href="#breaking-changes-0-1-0-9026"></a></h4>
 <ul><li>Updated function names to follow the pattern <code>ard_&lt;pkgname&gt;_&lt;fnname&gt;()</code>. Former functions names have <em>not</em> been deprecated. (<a href="https://github.com/insightsengineering/cardx/issues/106" class="external-link">#106</a>)</li>
 </ul><div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span></span>
@@ -70,7 +62,7 @@ <h4 id="breaking-changes-0-1-0-9025">Breaking Changes<a class="anchor" aria-labe
 <span><span class="fu">ard_moodtest</span><span class="op">(</span><span class="op">)</span>          <span class="op">-&gt;</span> <span class="fu"><a href="../reference/ard_stats_mood_test.html">ard_stats_mood_test</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
 </div>
 <div class="section level4">
-<h4 id="new-features-0-1-0-9025">New Features<a class="anchor" aria-label="anchor" href="#new-features-0-1-0-9025"></a></h4>
+<h4 id="new-features-0-1-0-9026">New Features<a class="anchor" aria-label="anchor" href="#new-features-0-1-0-9026"></a></h4>
 <ul><li>
 <p>Added the following functions for calculating Analysis Results Data (ARD).</p>
 <ul><li>
diff --git a/main/pkgdown.yml b/main/pkgdown.yml
index 7b65d3247..accddde7d 100644
--- a/main/pkgdown.yml
+++ b/main/pkgdown.yml
@@ -2,7 +2,7 @@ pandoc: 3.1.1
 pkgdown: 2.0.9
 pkgdown_sha: ~
 articles: {}
-last_built: 2024-04-21T03:46Z
+last_built: 2024-04-25T15:23Z
 urls:
   reference: https://insightsengineering.github.io/cardx/reference
   article: https://insightsengineering.github.io/cardx/articles
diff --git a/main/reference/ard_aod_wald_test.html b/main/reference/ard_aod_wald_test.html
index 094ba5df7..ba8e454fa 100644
--- a/main/reference/ard_aod_wald_test.html
+++ b/main/reference/ard_aod_wald_test.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cardx</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
     <div style="width: 140px; margin-left: 0.5rem;"> <small class="nav-text text-muted me-auto">part of</small> <img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/nest.png?raw=true" alt="NEST" style="height: 30px;"><a href="https://pharmaverse.org/" class="external-link"><img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/pharmaverse.png?raw=true" alt="pharmaverse" style="height: 28px;"></a> </div>
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -26,14 +26,6 @@
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-<!-- start dropdown for versions --> <li class="nav-item dropdown">
-        <a href="#" class="nav-link dropdown-toggle"
-          data-bs-toggle="dropdown" role="button"
-          aria-expanded="false" aria-haspopup="true"
-          id="dropdown-versions">Versions</a> <div class="dropdown-menu" aria-labelledby="dropdown-versions"> <a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/main">main</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/latest-tag">latest-tag</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/v0.1.0">v0.1.0</a> </div></li>
-<!-- end dropdown for versions -->
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         <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
 
diff --git a/main/reference/ard_car_anova.html b/main/reference/ard_car_anova.html
index 21ca7ee1e..7e5fbe35c 100644
--- a/main/reference/ard_car_anova.html
+++ b/main/reference/ard_car_anova.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cardx</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
     <div style="width: 140px; margin-left: 0.5rem;"> <small class="nav-text text-muted me-auto">part of</small> <img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/nest.png?raw=true" alt="NEST" style="height: 30px;"><a href="https://pharmaverse.org/" class="external-link"><img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/pharmaverse.png?raw=true" alt="pharmaverse" style="height: 28px;"></a> </div>
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -24,14 +24,6 @@
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-<!-- start dropdown for versions --> <li class="nav-item dropdown">
-        <a href="#" class="nav-link dropdown-toggle"
-          data-bs-toggle="dropdown" role="button"
-          aria-expanded="false" aria-haspopup="true"
-          id="dropdown-versions">Versions</a> <div class="dropdown-menu" aria-labelledby="dropdown-versions"> <a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/main">main</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/latest-tag">latest-tag</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/v0.1.0">v0.1.0</a> </div></li>
-<!-- end dropdown for versions -->
       </ul><form class="form-inline my-2 my-lg-0" role="search">
         <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
 
diff --git a/main/reference/ard_car_vif.html b/main/reference/ard_car_vif.html
index 601ec2c25..b26498b6e 100644
--- a/main/reference/ard_car_vif.html
+++ b/main/reference/ard_car_vif.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cardx</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
     <div style="width: 140px; margin-left: 0.5rem;"> <small class="nav-text text-muted me-auto">part of</small> <img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/nest.png?raw=true" alt="NEST" style="height: 30px;"><a href="https://pharmaverse.org/" class="external-link"><img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/pharmaverse.png?raw=true" alt="pharmaverse" style="height: 28px;"></a> </div>
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -26,14 +26,6 @@
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-<!-- start dropdown for versions --> <li class="nav-item dropdown">
-        <a href="#" class="nav-link dropdown-toggle"
-          data-bs-toggle="dropdown" role="button"
-          aria-expanded="false" aria-haspopup="true"
-          id="dropdown-versions">Versions</a> <div class="dropdown-menu" aria-labelledby="dropdown-versions"> <a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/main">main</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/latest-tag">latest-tag</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/v0.1.0">v0.1.0</a> </div></li>
-<!-- end dropdown for versions -->
       </ul><form class="form-inline my-2 my-lg-0" role="search">
         <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
 
diff --git a/main/reference/ard_effectsize_cohens_d.html b/main/reference/ard_effectsize_cohens_d.html
index 02add483b..19780658f 100644
--- a/main/reference/ard_effectsize_cohens_d.html
+++ b/main/reference/ard_effectsize_cohens_d.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cardx</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
     <div style="width: 140px; margin-left: 0.5rem;"> <small class="nav-text text-muted me-auto">part of</small> <img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/nest.png?raw=true" alt="NEST" style="height: 30px;"><a href="https://pharmaverse.org/" class="external-link"><img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/pharmaverse.png?raw=true" alt="pharmaverse" style="height: 28px;"></a> </div>
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -26,14 +26,6 @@
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-<!-- start dropdown for versions --> <li class="nav-item dropdown">
-        <a href="#" class="nav-link dropdown-toggle"
-          data-bs-toggle="dropdown" role="button"
-          aria-expanded="false" aria-haspopup="true"
-          id="dropdown-versions">Versions</a> <div class="dropdown-menu" aria-labelledby="dropdown-versions"> <a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/main">main</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/latest-tag">latest-tag</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/v0.1.0">v0.1.0</a> </div></li>
-<!-- end dropdown for versions -->
       </ul><form class="form-inline my-2 my-lg-0" role="search">
         <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
 
diff --git a/main/reference/ard_effectsize_hedges_g.html b/main/reference/ard_effectsize_hedges_g.html
index 419233c80..fe448adc6 100644
--- a/main/reference/ard_effectsize_hedges_g.html
+++ b/main/reference/ard_effectsize_hedges_g.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cardx</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
     <div style="width: 140px; margin-left: 0.5rem;"> <small class="nav-text text-muted me-auto">part of</small> <img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/nest.png?raw=true" alt="NEST" style="height: 30px;"><a href="https://pharmaverse.org/" class="external-link"><img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/pharmaverse.png?raw=true" alt="pharmaverse" style="height: 28px;"></a> </div>
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -26,14 +26,6 @@
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-<!-- start dropdown for versions --> <li class="nav-item dropdown">
-        <a href="#" class="nav-link dropdown-toggle"
-          data-bs-toggle="dropdown" role="button"
-          aria-expanded="false" aria-haspopup="true"
-          id="dropdown-versions">Versions</a> <div class="dropdown-menu" aria-labelledby="dropdown-versions"> <a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/main">main</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/latest-tag">latest-tag</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/v0.1.0">v0.1.0</a> </div></li>
-<!-- end dropdown for versions -->
       </ul><form class="form-inline my-2 my-lg-0" role="search">
         <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
 
diff --git a/main/reference/ard_emmeans_mean_difference.html b/main/reference/ard_emmeans_mean_difference.html
index cce173624..3cae2a9e3 100644
--- a/main/reference/ard_emmeans_mean_difference.html
+++ b/main/reference/ard_emmeans_mean_difference.html
@@ -24,7 +24,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cardx</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
     <div style="width: 140px; margin-left: 0.5rem;"> <small class="nav-text text-muted me-auto">part of</small> <img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/nest.png?raw=true" alt="NEST" style="height: 30px;"><a href="https://pharmaverse.org/" class="external-link"><img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/pharmaverse.png?raw=true" alt="pharmaverse" style="height: 28px;"></a> </div>
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -38,14 +38,6 @@
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-<!-- start dropdown for versions --> <li class="nav-item dropdown">
-        <a href="#" class="nav-link dropdown-toggle"
-          data-bs-toggle="dropdown" role="button"
-          aria-expanded="false" aria-haspopup="true"
-          id="dropdown-versions">Versions</a> <div class="dropdown-menu" aria-labelledby="dropdown-versions"> <a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/main">main</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/latest-tag">latest-tag</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/v0.1.0">v0.1.0</a> </div></li>
-<!-- end dropdown for versions -->
       </ul><form class="form-inline my-2 my-lg-0" role="search">
         <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
 
diff --git a/main/reference/ard_proportion_ci.html b/main/reference/ard_proportion_ci.html
index 5c260f72d..a1004644b 100644
--- a/main/reference/ard_proportion_ci.html
+++ b/main/reference/ard_proportion_ci.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cardx</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
     <div style="width: 140px; margin-left: 0.5rem;"> <small class="nav-text text-muted me-auto">part of</small> <img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/nest.png?raw=true" alt="NEST" style="height: 30px;"><a href="https://pharmaverse.org/" class="external-link"><img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/pharmaverse.png?raw=true" alt="pharmaverse" style="height: 28px;"></a> </div>
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -26,14 +26,6 @@
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-<!-- start dropdown for versions --> <li class="nav-item dropdown">
-        <a href="#" class="nav-link dropdown-toggle"
-          data-bs-toggle="dropdown" role="button"
-          aria-expanded="false" aria-haspopup="true"
-          id="dropdown-versions">Versions</a> <div class="dropdown-menu" aria-labelledby="dropdown-versions"> <a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/main">main</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/latest-tag">latest-tag</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/v0.1.0">v0.1.0</a> </div></li>
-<!-- end dropdown for versions -->
       </ul><form class="form-inline my-2 my-lg-0" role="search">
         <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
 
diff --git a/main/reference/ard_regression.html b/main/reference/ard_regression.html
index 159596c46..974a2e3e7 100644
--- a/main/reference/ard_regression.html
+++ b/main/reference/ard_regression.html
@@ -12,7 +12,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cardx</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
     <div style="width: 140px; margin-left: 0.5rem;"> <small class="nav-text text-muted me-auto">part of</small> <img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/nest.png?raw=true" alt="NEST" style="height: 30px;"><a href="https://pharmaverse.org/" class="external-link"><img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/pharmaverse.png?raw=true" alt="pharmaverse" style="height: 28px;"></a> </div>
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -26,14 +26,6 @@
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-<!-- start dropdown for versions --> <li class="nav-item dropdown">
-        <a href="#" class="nav-link dropdown-toggle"
-          data-bs-toggle="dropdown" role="button"
-          aria-expanded="false" aria-haspopup="true"
-          id="dropdown-versions">Versions</a> <div class="dropdown-menu" aria-labelledby="dropdown-versions"> <a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/main">main</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/latest-tag">latest-tag</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/v0.1.0">v0.1.0</a> </div></li>
-<!-- end dropdown for versions -->
       </ul><form class="form-inline my-2 my-lg-0" role="search">
         <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
 
diff --git a/main/reference/ard_regression_basic.html b/main/reference/ard_regression_basic.html
index 08787f97c..1b9c2badb 100644
--- a/main/reference/ard_regression_basic.html
+++ b/main/reference/ard_regression_basic.html
@@ -34,7 +34,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cardx</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
     <div style="width: 140px; margin-left: 0.5rem;"> <small class="nav-text text-muted me-auto">part of</small> <img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/nest.png?raw=true" alt="NEST" style="height: 30px;"><a href="https://pharmaverse.org/" class="external-link"><img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/pharmaverse.png?raw=true" alt="pharmaverse" style="height: 28px;"></a> </div>
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -48,14 +48,6 @@
 <li class="nav-item">
   <a class="nav-link" href="../news/index.html">Changelog</a>
 </li>
-<!-- start dropdown for versions --> <li class="nav-item dropdown">
-        <a href="#" class="nav-link dropdown-toggle"
-          data-bs-toggle="dropdown" role="button"
-          aria-expanded="false" aria-haspopup="true"
-          id="dropdown-versions">Versions</a> <div class="dropdown-menu" aria-labelledby="dropdown-versions"> <a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/main">main</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/latest-tag">latest-tag</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/v0.1.0">v0.1.0</a> </div></li>
-<!-- end dropdown for versions -->
       </ul><form class="form-inline my-2 my-lg-0" role="search">
         <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>
 
diff --git a/main/reference/ard_smd_smd.html b/main/reference/ard_smd_smd.html
index 3097286db..9bbba8a8d 100644
--- a/main/reference/ard_smd_smd.html
+++ b/main/reference/ard_smd_smd.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">cardx</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
     <div style="width: 140px; margin-left: 0.5rem;"> <small class="nav-text text-muted me-auto">part of</small> <img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/nest.png?raw=true" alt="NEST" style="height: 30px;"><a href="https://pharmaverse.org/" class="external-link"><img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/pharmaverse.png?raw=true" alt="pharmaverse" style="height: 28px;"></a> </div>
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@@ -24,14 +24,6 @@
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diff --git a/main/reference/ard_stats_anova.html b/main/reference/ard_stats_anova.html
index 148b7643a..1035b29fc 100644
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index 7c9c95e85..603dc09ab 100644
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index e594fd8c4..da1f141e4 100644
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@@ -12,7 +12,7 @@
     
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diff --git a/main/reference/ard_stats_kruskal_test.html b/main/reference/ard_stats_kruskal_test.html
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diff --git a/main/reference/ard_stats_mood_test.html b/main/reference/ard_stats_mood_test.html
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diff --git a/main/reference/ard_stats_wilcox_test.html b/main/reference/ard_stats_wilcox_test.html
index 5a2b45348..24f67f3e3 100644
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@@ -10,7 +10,7 @@
     
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diff --git a/main/reference/ard_survey_svychisq.html b/main/reference/ard_survey_svychisq.html
index cd5217b87..958aeed21 100644
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@@ -12,7 +12,7 @@
     
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diff --git a/main/reference/ard_survey_svycontinuous.html b/main/reference/ard_survey_svycontinuous.html
index 56314a8cc..d9345fd9d 100644
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@@ -10,7 +10,7 @@
     
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diff --git a/main/reference/ard_survey_svyranktest.html b/main/reference/ard_survey_svyranktest.html
index c631be6da..3ab99c829 100644
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diff --git a/main/reference/ard_survey_svyttest.html b/main/reference/ard_survey_svyttest.html
index 35070fc83..4a34c338c 100644
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@@ -10,7 +10,7 @@
     
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diff --git a/main/reference/ard_survival_survdiff.html b/main/reference/ard_survival_survdiff.html
index f3a8a0b2e..628f39d1a 100644
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@@ -10,7 +10,7 @@
     
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diff --git a/main/reference/ard_survival_survfit.html b/main/reference/ard_survival_survfit.html
index 46e276dd1..45293701e 100644
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@@ -12,7 +12,7 @@
     
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-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
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@@ -26,14 +26,6 @@
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diff --git a/main/reference/cardx-package.html b/main/reference/cardx-package.html
index e105bcbbb..6beae47b5 100644
--- a/main/reference/cardx-package.html
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-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
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diff --git a/main/reference/construction_helpers.html b/main/reference/construction_helpers.html
index 5dcfe1d2c..63488640b 100644
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@@ -24,14 +24,6 @@
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@@ -249,15 +241,14 @@ <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-e
 <span class="r-in"><span><span class="op">)</span> <span class="op">|&gt;</span></span></span>
 <span class="r-in"><span>  <span class="fu"><a href="ard_regression.html">ard_regression</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">dplyr</span><span class="fu">::</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">stat_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">"term"</span>, <span class="st">"estimate"</span>, <span class="st">"p.value"</span><span class="op">)</span><span class="op">)</span></span></span>
-<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #555555;">{cards} data frame: 6 x 7</span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span>   variable variable_level   context stat_name stat_label    stat</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 1    M P G             NA regressi…      term       term `M P G`</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 2    M P G             NA regressi…  estimate  Coeffici…  -2.775</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 3    M P G             NA regressi…   p.value    p-value   0.213</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 4      cyl             NA regressi…      term       term     cyl</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 5      cyl             NA regressi…  estimate  Coeffici…  23.979</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 6      cyl             NA regressi…   p.value    p-value   0.003</span>
-<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #00BBBB;">ℹ</span> <span style="color: #555555;">1 more variable: fmt_fn</span></span>
+<span class="r-msg co"><span class="r-pr">#&gt;</span> <span style="color: #555555;">{cards} data frame: 6 x 6</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span>   variable   context stat_name stat_label    stat fmt_fn</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 1    M P G regressi…      term       term `M P G`   NULL</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 2    M P G regressi…  estimate  Coeffici…  -2.775      1</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 3    M P G regressi…   p.value    p-value   0.213      1</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 4      cyl regressi…      term       term     cyl   NULL</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 5      cyl regressi…  estimate  Coeffici…  23.979      1</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 6      cyl regressi…   p.value    p-value   0.003      1</span>
 </code></pre></div>
     </div>
   </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
diff --git a/main/reference/dot-extract_wald_results.html b/main/reference/dot-extract_wald_results.html
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diff --git a/main/reference/dot-format_cohens_d_results.html b/main/reference/dot-format_cohens_d_results.html
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diff --git a/main/reference/dot-format_hedges_g_results.html b/main/reference/dot-format_hedges_g_results.html
index f0432d06f..a0c73d1f7 100644
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@@ -10,7 +10,7 @@
     
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+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
     <div style="width: 140px; margin-left: 0.5rem;"> <small class="nav-text text-muted me-auto">part of</small> <img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/nest.png?raw=true" alt="NEST" style="height: 30px;"><a href="https://pharmaverse.org/" class="external-link"><img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/pharmaverse.png?raw=true" alt="pharmaverse" style="height: 28px;"></a> </div>
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-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/v0.1.0">v0.1.0</a> </div></li>
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diff --git a/main/reference/dot-format_mcnemartest_results.html b/main/reference/dot-format_mcnemartest_results.html
index a73a935e9..f273ccce8 100644
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+++ b/main/reference/dot-format_mcnemartest_results.html
@@ -10,7 +10,7 @@
     
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-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
     <div style="width: 140px; margin-left: 0.5rem;"> <small class="nav-text text-muted me-auto">part of</small> <img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/nest.png?raw=true" alt="NEST" style="height: 30px;"><a href="https://pharmaverse.org/" class="external-link"><img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/pharmaverse.png?raw=true" alt="pharmaverse" style="height: 28px;"></a> </div>
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-          data-bs-toggle="dropdown" role="button"
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-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/v0.1.0">v0.1.0</a> </div></li>
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diff --git a/main/reference/dot-format_moodtest_results.html b/main/reference/dot-format_moodtest_results.html
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-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
     <div style="width: 140px; margin-left: 0.5rem;"> <small class="nav-text text-muted me-auto">part of</small> <img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/nest.png?raw=true" alt="NEST" style="height: 30px;"><a href="https://pharmaverse.org/" class="external-link"><img src="https://github.com/insightsengineering/hex-stickers/blob/main/PNG/pharmaverse.png?raw=true" alt="pharmaverse" style="height: 28px;"></a> </div>
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-        <a href="#" class="nav-link dropdown-toggle"
-          data-bs-toggle="dropdown" role="button"
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-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/v0.1.0">v0.1.0</a> </div></li>
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diff --git a/main/reference/dot-format_proptest_results.html b/main/reference/dot-format_proptest_results.html
index ca1734720..76e2b19b9 100644
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@@ -10,7 +10,7 @@
     
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-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
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diff --git a/main/reference/dot-format_survfit_results.html b/main/reference/dot-format_survfit_results.html
index 7e5de6773..f187d06ef 100644
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+++ b/main/reference/dot-format_survfit_results.html
@@ -10,7 +10,7 @@
     
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-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
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@@ -24,14 +24,6 @@
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-        <a href="#" class="nav-link dropdown-toggle"
-          data-bs-toggle="dropdown" role="button"
-          aria-expanded="false" aria-haspopup="true"
-          id="dropdown-versions">Versions</a> <div class="dropdown-menu" aria-labelledby="dropdown-versions"> <a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/main">main</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/latest-tag">latest-tag</a>
-<a class="dropdown-item" data-toggle="tooltip" title="" href="https://insightsengineering.github.io/cardx/v0.1.0">v0.1.0</a> </div></li>
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diff --git a/main/reference/dot-format_ttest_results.html b/main/reference/dot-format_ttest_results.html
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@@ -10,7 +10,7 @@
     
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+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.1.0.9026</small>
 
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 </li>
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-          data-bs-toggle="dropdown" role="button"
-          aria-expanded="false" aria-haspopup="true"
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-<!-- end dropdown for versions -->
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diff --git a/main/reference/dot-format_wilcoxtest_results.html b/main/reference/dot-format_wilcoxtest_results.html
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@@ -10,7 +10,7 @@
     
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diff --git a/main/search.json b/main/search.json
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Community leaders right responsibility remove, edit, reject comments, commits, code, wiki edits, issues, contributions aligned Code Conduct, communicate reasons moderation decisions appropriate.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CODE_OF_CONDUCT.html","id":"scope","dir":"","previous_headings":"","what":"Scope","title":"Contributor Covenant Code of Conduct","text":"Code Conduct applies within community spaces, also applies individual officially representing community public spaces. Examples representing community include using official e-mail address, posting via official social media account, acting appointed representative online offline event.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CODE_OF_CONDUCT.html","id":"enforcement","dir":"","previous_headings":"","what":"Enforcement","title":"Contributor Covenant Code of Conduct","text":"Instances abusive, harassing, otherwise unacceptable behavior may reported community leaders responsible enforcement [INSERT CONTACT METHOD]. complaints reviewed investigated promptly fairly. community leaders obligated respect privacy security reporter incident.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CODE_OF_CONDUCT.html","id":"enforcement-guidelines","dir":"","previous_headings":"","what":"Enforcement Guidelines","title":"Contributor Covenant Code of Conduct","text":"Community leaders follow Community Impact Guidelines determining consequences action deem violation Code Conduct:","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CODE_OF_CONDUCT.html","id":"id_1-correction","dir":"","previous_headings":"Enforcement Guidelines","what":"1. Correction","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Use inappropriate language behavior deemed unprofessional unwelcome community. Consequence: private, written warning community leaders, providing clarity around nature violation explanation behavior inappropriate. public apology may requested.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CODE_OF_CONDUCT.html","id":"id_2-warning","dir":"","previous_headings":"Enforcement Guidelines","what":"2. Warning","title":"Contributor Covenant Code of Conduct","text":"Community Impact: violation single incident series actions. Consequence: warning consequences continued behavior. interaction people involved, including unsolicited interaction enforcing Code Conduct, specified period time. includes avoiding interactions community spaces well external channels like social media. Violating terms may lead temporary permanent ban.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CODE_OF_CONDUCT.html","id":"id_3-temporary-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"3. Temporary Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: serious violation community standards, including sustained inappropriate behavior. Consequence: temporary ban sort interaction public communication community specified period time. public private interaction people involved, including unsolicited interaction enforcing Code Conduct, allowed period. Violating terms may lead permanent ban.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CODE_OF_CONDUCT.html","id":"id_4-permanent-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"4. Permanent Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Demonstrating pattern violation community standards, including sustained inappropriate behavior, harassment individual, aggression toward disparagement classes individuals. Consequence: permanent ban sort public interaction within community.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CODE_OF_CONDUCT.html","id":"attribution","dir":"","previous_headings":"","what":"Attribution","title":"Contributor Covenant Code of Conduct","text":"Code Conduct adapted Contributor Covenant, version 2.1, available https://www.contributor-covenant.org/version/2/1/code_of_conduct.html. Community Impact Guidelines inspired Mozilla’s code conduct enforcement ladder. answers common questions code conduct, see FAQ https://www.contributor-covenant.org/faq. Translations available https://www.contributor-covenant.org/translations.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CONTRIBUTING.html","id":null,"dir":"","previous_headings":"","what":"Contribution Guidelines","title":"Contribution Guidelines","text":"🙏 Thank taking time contribute! input deeply valued, whether issue, pull request, even feedback, regardless size, content scope.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CONTRIBUTING.html","id":"table-of-contents","dir":"","previous_headings":"","what":"Table of contents","title":"Contribution Guidelines","text":"👶 Getting started 📔 Code Conduct 🗃 License 📜 Issues 🚩 Pull requests 💻 Coding guidelines 🏆 Recognition model ❓ Questions","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CONTRIBUTING.html","id":"getting-started","dir":"","previous_headings":"","what":"Getting started","title":"Contribution Guidelines","text":"Please refer project documentation brief introduction. Please also see articles within project documentation additional information.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CONTRIBUTING.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Contribution Guidelines","text":"Code Conduct governs project. Participants contributors expected follow rules outlined therein.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CONTRIBUTING.html","id":"license","dir":"","previous_headings":"","what":"License","title":"Contribution Guidelines","text":"contributions covered project’s license.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CONTRIBUTING.html","id":"issues","dir":"","previous_headings":"","what":"Issues","title":"Contribution Guidelines","text":"use GitHub track issues, feature requests, bugs. submitting new issue, please check issue already reported. issue already exists, please upvote existing issue 👍. new feature requests, please elaborate context benefit feature users, developers, relevant personas.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/cardx/main/CONTRIBUTING.html","id":"github-flow","dir":"","previous_headings":"Pull requests","what":"GitHub Flow","title":"Contribution Guidelines","text":"repository uses GitHub Flow model collaboration. submit pull request: Create branch Please see branch naming convention . don’t write access repository, please fork . Make changes Make sure code passes checks imposed GitHub Actions well documented well tested unit tests sufficiently covering changes introduced Create pull request (PR) pull request description, please link relevant issue (), provide detailed description change, include assumptions. Address review comments, Post approval Merge PR write access. Otherwise, reviewer merge PR behalf. Pat back Congratulations! 🎉 now official contributor project! grateful contribution.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CONTRIBUTING.html","id":"branch-naming-convention","dir":"","previous_headings":"Pull requests","what":"Branch naming convention","title":"Contribution Guidelines","text":"Suppose changes related current issue current project; please name branch follows: <issue_id>_<short_description>. Please use underscore (_) delimiter word separation. example, 420_fix_ui_bug suitable branch name change resolving UI-related bug reported issue number 420 current project. change affects multiple repositories, please name branches follows: <issue_id>_<issue_repo>_<short description>. example, 69_awesomeproject_fix_spelling_error reference issue 69 reported project awesomeproject aims resolve one spelling errors multiple (likely related) repositories.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CONTRIBUTING.html","id":"monorepo-and-stageddependencies","dir":"","previous_headings":"Pull requests","what":"monorepo and staged.dependencies","title":"Contribution Guidelines","text":"Sometimes might need change upstream dependent package(s) able submit meaningful change. using staged.dependencies functionality simulate monorepo behavior. dependency configuration already specified project’s staged_dependencies.yaml file. need name feature branches appropriately. exception branch naming convention described . Please refer staged.dependencies package documentation details.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CONTRIBUTING.html","id":"coding-guidelines","dir":"","previous_headings":"","what":"Coding guidelines","title":"Contribution Guidelines","text":"repository follows unified processes standards adopted maintainers ensure software development carried consistently within teams cohesively across repositories.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CONTRIBUTING.html","id":"style-guide","dir":"","previous_headings":"Coding guidelines","what":"Style guide","title":"Contribution Guidelines","text":"repository follows standard tidyverse style guide uses lintr lint checks. Customized lint configurations available repository’s .lintr file.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CONTRIBUTING.html","id":"dependency-management","dir":"","previous_headings":"Coding guidelines","what":"Dependency management","title":"Contribution Guidelines","text":"Lightweight right weight. repository follows tinyverse recommedations limiting dependencies minimum.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CONTRIBUTING.html","id":"dependency-version-management","dir":"","previous_headings":"Coding guidelines","what":"Dependency version management","title":"Contribution Guidelines","text":"code compatible (!) historical versions given dependenct package, required specify minimal version DESCRIPTION file. particular: development version requires (imports) development version another package - required put abc (>= 1.2.3.9000).","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/cardx/main/CONTRIBUTING.html","id":"r--package-versions","dir":"","previous_headings":"Coding guidelines > Recommended development environment & tools","what":"R & package versions","title":"Contribution Guidelines","text":"continuously test packages newest R version along recent dependencies CRAN BioConductor. recommend working environment also set way. can find details R version packages used R CMD check GitHub Action execution log - step prints R sessionInfo(). discover bugs older R versions older set dependencies, please create relevant bug reports.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CONTRIBUTING.html","id":"pre-commit","dir":"","previous_headings":"Coding guidelines > Recommended development environment & tools","what":"pre-commit","title":"Contribution Guidelines","text":"highly recommend use pre-commit tool combined R hooks pre-commit execute checks committing pushing changes. Pre-commit hooks already available repository’s .pre-commit-config.yaml file.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CONTRIBUTING.html","id":"recognition-model","dir":"","previous_headings":"","what":"Recognition model","title":"Contribution Guidelines","text":"mentioned previously, contributions deeply valued appreciated. contribution data available part repository insights, recognize significant contribution hence add contributor package authors list, following rules enforced: Minimum 5% lines code authored* (determined git blame query) top 5 contributors terms number commits lines added lines removed* *Excluding auto-generated code, including limited roxygen comments renv.lock files. package maintainer also reserves right adjust criteria recognize contributions.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/CONTRIBUTING.html","id":"questions","dir":"","previous_headings":"","what":"Questions","title":"Contribution Guidelines","text":"questions regarding contribution guidelines, please contact package/repository maintainer.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/cardx/main/SECURITY.html","id":"reporting-security-issues","dir":"","previous_headings":"","what":"Reporting Security Issues","title":"Security Policy","text":"believe found security vulnerability repositories organization, please report us coordinated disclosure. Please report security vulnerabilities public GitHub issues, discussions, pull requests. Instead, please send email vulnerability.management[@]roche.com. Please include much information listed can help us better understand resolve issue: type issue (e.g., buffer overflow, SQL injection, cross-site scripting) Full paths source file(s) related manifestation issue location affected source code (tag/branch/commit direct URL) special configuration required reproduce issue Step--step instructions reproduce issue Proof--concept exploit code (possible) Impact issue, including attacker might exploit issue information help us triage report quickly.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/SECURITY.html","id":"data-security-standards-dss","dir":"","previous_headings":"","what":"Data Security Standards (DSS)","title":"Security Policy","text":"Please make sure reporting issues form bug, feature, pull request, sensitive information PII, PHI, PCI completely removed text attachments, including pictures videos.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Daniel Sjoberg. Author, maintainer. Abinaya Yogasekaram. Author. Emily de la Rua. Author. F. Hoffmann-La Roche AG. Copyright holder, funder.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Sjoberg D, Yogasekaram , de la Rua E (2024). cardx: Extra Analysis Results Data Utilities. R package version 0.1.0.9025, https://github.com/insightsengineering/cardx.","code":"@Manual{,   title = {cardx: Extra Analysis Results Data Utilities},   author = {Daniel Sjoberg and Abinaya Yogasekaram and Emily {de la Rua}},   year = {2024},   note = {R package version 0.1.0.9025},   url = {https://github.com/insightsengineering/cardx}, }"},{"path":"https://insightsengineering.github.io/cardx/main/index.html","id":"cardx-","dir":"","previous_headings":"","what":"Extra Analysis Results Data Utilities","title":"Extra Analysis Results Data Utilities","text":"source repository cardx R package.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Extra Analysis Results Data Utilities","text":"latest development version cardx can directly installed GitHub running following:","code":"if (!require(\"pak\")) install.packages(\"pak\") pak::pak(\"insightsengineering/cardx\")"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_aod_wald_test.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Wald Test — ard_aod_wald_test","title":"ARD Wald Test — ard_aod_wald_test","text":"Function takes regression model object calculates Wald statistical test using aod::wald.test().","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_aod_wald_test.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Wald Test — ard_aod_wald_test","text":"","code":"ard_aod_wald_test(x, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_aod_wald_test.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Wald Test — ard_aod_wald_test","text":"x regression model object ... arguments passed aod::wald.test(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_aod_wald_test.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Wald Test — ard_aod_wald_test","text":"data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_aod_wald_test.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Wald Test — ard_aod_wald_test","text":"","code":"lm(AGE ~ ARM, data = cards::ADSL) |>   ard_aod_wald_test() #> {cards} data frame: 6 x 8 #>      variable   context stat_name stat_label     stat fmt_fn #> 1 (Intercept) aod_wald…        df  Degrees …        1      1 #> 2 (Intercept) aod_wald… statistic  Statistic 7126.713      1 #> 3 (Intercept) aod_wald…   p.value    p-value        0      1 #> 4         ARM aod_wald…        df  Degrees …        2      1 #> 5         ARM aod_wald… statistic  Statistic    1.046      1 #> 6         ARM aod_wald…   p.value    p-value    0.593      1 #> ℹ 2 more variables: warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_car_anova.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD ANOVA from car Package — ard_car_anova","title":"ARD ANOVA from car Package — ard_car_anova","text":"Function takes regression model object calculated ANOVA using car::Anova().","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_car_anova.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD ANOVA from car Package — ard_car_anova","text":"","code":"ard_car_anova(x, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_car_anova.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD ANOVA from car Package — ard_car_anova","text":"x regression model object ... arguments passed car::Anova(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_car_anova.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD ANOVA from car Package — ard_car_anova","text":"data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_car_anova.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD ANOVA from car Package — ard_car_anova","text":"","code":"lm(AGE ~ ARM, data = cards::ADSL) |>   ard_car_anova() #> {cards} data frame: 5 x 8 #>   variable   context stat_name stat_label   stat fmt_fn #> 1      ARM car_anova     sumsq      sumsq 71.386      1 #> 2      ARM car_anova        df  Degrees …      2      1 #> 3      ARM car_anova    meansq     meansq 35.693      1 #> 4      ARM car_anova statistic  Statistic  0.523      1 #> 5      ARM car_anova   p.value    p-value  0.593      1 #> ℹ 2 more variables: warning, error  glm(vs ~ factor(cyl) + factor(am), data = mtcars, family = binomial) |>   ard_car_anova(test.statistic = \"Wald\") #> {cards} data frame: 6 x 8 #>      variable   context stat_name stat_label  stat   warning #> 1 factor(cyl) car_anova statistic  Statistic     0 glm.fit:… #> 2 factor(cyl) car_anova        df  Degrees …     2 glm.fit:… #> 3 factor(cyl) car_anova   p.value    p-value     1 glm.fit:… #> 4  factor(am) car_anova statistic  Statistic     0 glm.fit:… #> 5  factor(am) car_anova        df  Degrees …     1 glm.fit:… #> 6  factor(am) car_anova   p.value    p-value 0.998 glm.fit:… #> ℹ 2 more variables: fmt_fn, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_car_vif.html","id":null,"dir":"Reference","previous_headings":"","what":"Regression VIF ARD — ard_car_vif","title":"Regression VIF ARD — ard_car_vif","text":"Function takes regression model object returns variance inflation factor (VIF) using car::vif() converts ARD structure","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_car_vif.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Regression VIF ARD — ard_car_vif","text":"","code":"ard_car_vif(x, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_car_vif.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Regression VIF ARD — ard_car_vif","text":"x regression model object See car::vif() details ... arguments passed car::vif(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_car_vif.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Regression VIF ARD — ard_car_vif","text":"data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_car_vif.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Regression VIF ARD — ard_car_vif","text":"","code":"lm(AGE ~ ARM + SEX, data = cards::ADSL) |>   ard_car_vif() #> {cards} data frame: 6 x 8 #>   variable context stat_name stat_label  stat fmt_fn #> 1      ARM car_vif      GVIF       GVIF 1.016      1 #> 2      ARM car_vif        df         df     2      1 #> 3      ARM car_vif     aGVIF  Adjusted… 1.004      1 #> 4      SEX car_vif      GVIF       GVIF 1.016      1 #> 5      SEX car_vif        df         df     1      1 #> 6      SEX car_vif     aGVIF  Adjusted… 1.008      1 #> ℹ 2 more variables: warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_effectsize_cohens_d.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Cohen's D Test — ard_effectsize_cohens_d","title":"ARD Cohen's D Test — ard_effectsize_cohens_d","text":"Analysis results data paired non-paired Cohen's D Effect Size Test using effectsize::cohens_d().","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_effectsize_cohens_d.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Cohen's D Test — ard_effectsize_cohens_d","text":"","code":"ard_effectsize_cohens_d(data, by, variables, ...)  ard_effectsize_paired_cohens_d(data, by, variables, id, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_effectsize_cohens_d.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Cohen's D Test — ard_effectsize_cohens_d","text":"data (data.frame) data frame. See details. (tidy-select) column name compare . Must categorical variable exactly two levels. variables (tidy-select) column names compared. Must continuous variables. Independent tests run variable. ... arguments passed effectsize::cohens_d(...) id (tidy-select) column name subject participant ID","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_effectsize_cohens_d.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Cohen's D Test — ard_effectsize_cohens_d","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_effectsize_cohens_d.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"ARD Cohen's D Test — ard_effectsize_cohens_d","text":"ard_effectsize_cohens_d() function, data expected one row per subject. data passed effectsize::cohens_d(data[[variable]]~data[[]], data, paired = FALSE, ...). ard_effectsize_paired_cohens_d() function, data expected one row per subject per level. effect size calculated, data reshaped wide format one row per subject. data passed effectsize::cohens_d(x = data_wide[[<level 1>]], y = data_wide[[<level 2>]], paired = TRUE, ...).","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_effectsize_cohens_d.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Cohen's D Test — ard_effectsize_cohens_d","text":"","code":"cards::ADSL |>   dplyr::filter(ARM %in% c(\"Placebo\", \"Xanomeline High Dose\")) |>   ard_effectsize_cohens_d(by = ARM, variables = AGE) #> {cards} data frame: 8 x 9 #>   group1 variable   context   stat_name stat_label      stat #> 1    ARM      AGE effectsi…    estimate  Effect S…       0.1 #> 2    ARM      AGE effectsi…  conf.level  CI Confi…      0.95 #> 3    ARM      AGE effectsi…    conf.low  CI Lower…    -0.201 #> 4    ARM      AGE effectsi…   conf.high  CI Upper…     0.401 #> 5    ARM      AGE effectsi…          mu    H0 Mean         0 #> 6    ARM      AGE effectsi…      paired  Paired t…     FALSE #> 7    ARM      AGE effectsi…   pooled_sd  Pooled S…      TRUE #> 8    ARM      AGE effectsi… alternative  Alternat… two.sided #> ℹ 3 more variables: fmt_fn, warning, error  # constructing a paired data set, # where patients receive both treatments cards::ADSL[c(\"ARM\", \"AGE\")] |>   dplyr::filter(ARM %in% c(\"Placebo\", \"Xanomeline High Dose\")) |>   dplyr::mutate(.by = ARM, USUBJID = dplyr::row_number()) |>   dplyr::arrange(USUBJID, ARM) |>   dplyr::group_by(USUBJID) |>   dplyr::filter(dplyr::n() > 1) |>   ard_effectsize_paired_cohens_d(by = ARM, variables = AGE, id = USUBJID) #> {cards} data frame: 8 x 9 #>   group1 variable   context   stat_name stat_label      stat #> 1    ARM      AGE effectsi…    estimate  Effect S…     0.069 #> 2    ARM      AGE effectsi…  conf.level  CI Confi…      0.95 #> 3    ARM      AGE effectsi…    conf.low  CI Lower…    -0.146 #> 4    ARM      AGE effectsi…   conf.high  CI Upper…     0.282 #> 5    ARM      AGE effectsi…          mu    H0 Mean         0 #> 6    ARM      AGE effectsi…      paired  Paired t…      TRUE #> 7    ARM      AGE effectsi…   pooled_sd  Pooled S…      TRUE #> 8    ARM      AGE effectsi… alternative  Alternat… two.sided #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_effectsize_hedges_g.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Hedge's G Test — ard_effectsize_hedges_g","title":"ARD Hedge's G Test — ard_effectsize_hedges_g","text":"Analysis results data paired non-paired Hedge's G Effect Size Test using effectsize::hedges_g().","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_effectsize_hedges_g.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Hedge's G Test — ard_effectsize_hedges_g","text":"","code":"ard_effectsize_hedges_g(data, by, variables, ...)  ard_effectsize_paired_hedges_g(data, by, variables, id, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_effectsize_hedges_g.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Hedge's G Test — ard_effectsize_hedges_g","text":"data (data.frame) data frame. See details. (tidy-select) column name compare . Must categorical variable exactly two levels. variables (tidy-select) column names compared. Must continuous variable. Independent tests run variable ... arguments passed effectsize::hedges_g(...) id (tidy-select) column name subject participant ID","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_effectsize_hedges_g.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Hedge's G Test — ard_effectsize_hedges_g","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_effectsize_hedges_g.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"ARD Hedge's G Test — ard_effectsize_hedges_g","text":"ard_effectsize_hedges_g() function, data expected one row per subject. data passed effectsize::hedges_g(data[[variable]]~data[[]], data, paired = FALSE, ...). ard_effectsize_paired_hedges_g() function, data expected one row per subject per level. effect size calculated, data reshaped wide format one row per subject. data passed effectsize::hedges_g(x = data_wide[[<level 1>]], y = data_wide[[<level 2>]], paired = TRUE, ...).","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_effectsize_hedges_g.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Hedge's G Test — ard_effectsize_hedges_g","text":"","code":"cards::ADSL |>   dplyr::filter(ARM %in% c(\"Placebo\", \"Xanomeline High Dose\")) |>   ard_effectsize_hedges_g(by = ARM, variables = AGE) #> {cards} data frame: 8 x 9 #>   group1 variable   context   stat_name stat_label      stat #> 1    ARM      AGE effectsi…    estimate  Effect S…       0.1 #> 2    ARM      AGE effectsi…  conf.level  CI Confi…      0.95 #> 3    ARM      AGE effectsi…    conf.low  CI Lower…      -0.2 #> 4    ARM      AGE effectsi…   conf.high  CI Upper…     0.399 #> 5    ARM      AGE effectsi…          mu    H0 Mean         0 #> 6    ARM      AGE effectsi…      paired  Paired t…     FALSE #> 7    ARM      AGE effectsi…   pooled_sd  Pooled S…      TRUE #> 8    ARM      AGE effectsi… alternative  Alternat… two.sided #> ℹ 3 more variables: fmt_fn, warning, error  # constructing a paired data set, # where patients receive both treatments cards::ADSL[c(\"ARM\", \"AGE\")] |>   dplyr::filter(ARM %in% c(\"Placebo\", \"Xanomeline High Dose\")) |>   dplyr::mutate(.by = ARM, USUBJID = dplyr::row_number()) |>   dplyr::arrange(USUBJID, ARM) |>   dplyr::group_by(USUBJID) |>   dplyr::filter(dplyr::n() > 1) |>   ard_effectsize_paired_hedges_g(by = ARM, variables = AGE, id = USUBJID) #> {cards} data frame: 8 x 9 #>   group1 variable   context   stat_name stat_label      stat #> 1    ARM      AGE effectsi…    estimate  Effect S…     0.068 #> 2    ARM      AGE effectsi…  conf.level  CI Confi…      0.95 #> 3    ARM      AGE effectsi…    conf.low  CI Lower…    -0.144 #> 4    ARM      AGE effectsi…   conf.high  CI Upper…      0.28 #> 5    ARM      AGE effectsi…          mu    H0 Mean         0 #> 6    ARM      AGE effectsi…      paired  Paired t…      TRUE #> 7    ARM      AGE effectsi…   pooled_sd  Pooled S…      TRUE #> 8    ARM      AGE effectsi… alternative  Alternat… two.sided #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_emmeans_mean_difference.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD for LS Mean Difference — ard_emmeans_mean_difference","title":"ARD for LS Mean Difference — ard_emmeans_mean_difference","text":"function calculates least-squares mean differences using 'emmeans' package using following   arguments data, formula, method, method.args, package used construct regression model via cardx::construct_model().","code":"emmeans::emmeans(object = <regression model>, specs = ~ <primary covariate>) |>   emmeans::contrast(method = \"pairwise\") |>   summary(infer = TRUE, level = <confidence level>)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_emmeans_mean_difference.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD for LS Mean Difference — ard_emmeans_mean_difference","text":"","code":"ard_emmeans_mean_difference(   data,   formula,   method,   method.args = list(),   package = \"base\",   response_type = c(\"continuous\", \"dichotomous\"),   conf.level = 0.95,   primary_covariate = getElement(attr(stats::terms(formula), \"term.labels\"), 1L) )"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_emmeans_mean_difference.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD for LS Mean Difference — ard_emmeans_mean_difference","text":"data (data.frame/survey.design) data frame survey design object formula (formula) formula method (string) string naming function called, e.g. \"glm\". function belongs library attached, package name must specified package argument. method.args (named list) named list arguments passed fn. package (string) string package name temporarily loaded function specified method executed. response_type (string) string indicating whether model outcome 'continuous' 'dichotomous'. 'dichotomous', call emmeans::emmeans() supplemented argument regrid=\"response\". conf.level (scalar numeric) confidence level confidence interval. Default 0.95. primary_covariate (string) string indicating primary covariate (typically dichotomous treatment variable). Default first covariate listed formula.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_emmeans_mean_difference.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD for LS Mean Difference — ard_emmeans_mean_difference","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_emmeans_mean_difference.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD for LS Mean Difference — ard_emmeans_mean_difference","text":"","code":"ard_emmeans_mean_difference(   data = mtcars,   formula = mpg ~ am + cyl,   method = \"lm\" ) #> {cards} data frame: 8 x 10 #>   group1 variable variable_level  stat_name stat_label      stat #> 1     am contrast      am0 - am1   estimate  Mean Dif…    -2.567 #> 2     am contrast      am0 - am1  std.error  std.error     1.291 #> 3     am contrast      am0 - am1         df         df        29 #> 4     am contrast      am0 - am1   conf.low  CI Lower…    -5.208 #> 5     am contrast      am0 - am1  conf.high  CI Upper…     0.074 #> 6     am contrast      am0 - am1    p.value    p-value     0.056 #> 7     am contrast      am0 - am1 conf.level  CI Confi…      0.95 #> 8     am contrast      am0 - am1     method     method Least-sq… #> ℹ 4 more variables: context, fmt_fn, warning, error  ard_emmeans_mean_difference(   data = mtcars,   formula = vs ~ am + mpg,   method = \"glm\",   method.args = list(family = binomial),   response_type = \"dichotomous\" ) #> {cards} data frame: 8 x 10 #>   group1 variable variable_level  stat_name stat_label      stat #> 1     am contrast      am0 - am1   estimate  Mean Dif…      0.61 #> 2     am contrast      am0 - am1  std.error  std.error     0.229 #> 3     am contrast      am0 - am1         df         df       Inf #> 4     am contrast      am0 - am1   conf.low  CI Lower…     0.162 #> 5     am contrast      am0 - am1  conf.high  CI Upper…     1.059 #> 6     am contrast      am0 - am1    p.value    p-value     0.008 #> 7     am contrast      am0 - am1 conf.level  CI Confi…      0.95 #> 8     am contrast      am0 - am1     method     method Least-sq… #> ℹ 4 more variables: context, fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_proportion_ci.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Proportion Confidence Intervals — ard_proportion_ci","title":"ARD Proportion Confidence Intervals — ard_proportion_ci","text":"Calculate confidence intervals proportions.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_proportion_ci.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Proportion Confidence Intervals — ard_proportion_ci","text":"","code":"ard_proportion_ci(   data,   variables,   by = dplyr::group_vars(data),   conf.level = 0.95,   strata,   weights = NULL,   max.iterations = 10,   method = c(\"waldcc\", \"wald\", \"clopper-pearson\", \"wilson\", \"wilsoncc\", \"strat_wilson\",     \"strat_wilsoncc\", \"agresti-coull\", \"jeffreys\") )"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_proportion_ci.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Proportion Confidence Intervals — ard_proportion_ci","text":"data (data.frame) data frame variables (tidy-select) columns include summaries. Columns must class <logical> <numeric> values coded c(0, 1). (tidy-select) columns stratify calculations conf.level (numeric) scalar (0, 1) indicating confidence level. Default 0.95 strata, weights, max.iterations arguments passed proportion_ci_strat_wilson(), method='strat_wilson' method (string) string indicating type confidence interval calculate. Must one 'waldcc', 'wald', 'clopper-pearson', 'wilson', 'wilsoncc', 'strat_wilson', 'strat_wilsoncc', 'agresti-coull', 'jeffreys'. See ?proportion_ci details.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_proportion_ci.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Proportion Confidence Intervals — ard_proportion_ci","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_proportion_ci.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Proportion Confidence Intervals — ard_proportion_ci","text":"","code":"ard_proportion_ci(mtcars, variables = c(vs, am), method = \"wilson\") #> {cards} data frame: 20 x 8 #>    variable   context   stat_name stat_label      stat fmt_fn #> 1        vs proporti…           N          N        32      0 #> 2        vs proporti…  conf.level  conf.lev…      0.95      1 #> 3        vs proporti…    estimate   estimate     0.438      1 #> 4        vs proporti…   statistic  statistic       0.5      1 #> 5        vs proporti…     p.value    p.value      0.48      1 #> 6        vs proporti…   parameter  parameter         1      0 #> 7        vs proporti…    conf.low   conf.low     0.282      1 #> 8        vs proporti…   conf.high  conf.high     0.607      1 #> 9        vs proporti…      method     method Wilson C…   <fn> #> 10       vs proporti… alternative  alternat… two.sided   <fn> #> 11       am proporti…           N          N        32      0 #> 12       am proporti…  conf.level  conf.lev…      0.95      1 #> 13       am proporti…    estimate   estimate     0.406      1 #> 14       am proporti…   statistic  statistic     1.125      1 #> 15       am proporti…     p.value    p.value     0.289      1 #> 16       am proporti…   parameter  parameter         1      0 #> 17       am proporti…    conf.low   conf.low     0.255      1 #> 18       am proporti…   conf.high  conf.high     0.577      1 #> 19       am proporti…      method     method Wilson C…   <fn> #> 20       am proporti… alternative  alternat… two.sided   <fn> #> ℹ 2 more variables: warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_regression.html","id":null,"dir":"Reference","previous_headings":"","what":"Regression ARD — ard_regression","title":"Regression ARD — ard_regression","text":"Function takes regression model object converts ARD structure using broom.helpers package.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_regression.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Regression ARD — ard_regression","text":"","code":"ard_regression(x, ...)  # S3 method for default ard_regression(x, tidy_fun = broom.helpers::tidy_with_broom_or_parameters, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_regression.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Regression ARD — ard_regression","text":"x regression model object ... Arguments passed broom.helpers::tidy_plus_plus() tidy_fun (function) tidier. Default broom.helpers::tidy_with_broom_or_parameters","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_regression.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Regression ARD — ard_regression","text":"data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_regression.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Regression ARD — ard_regression","text":"","code":"lm(AGE ~ ARM, data = cards::ADSL) |>   ard_regression(add_estimate_to_reference_rows = TRUE) #> {cards} data frame: 43 x 7 #>    variable variable_level   context      stat_name stat_label      stat #> 1       ARM        Placebo regressi…           term       term ARMPlace… #> 2       ARM        Placebo regressi…      var_label      Label Descript… #> 3       ARM        Placebo regressi…      var_class      Class character #> 4       ARM        Placebo regressi…       var_type       Type categori… #> 5       ARM        Placebo regressi…    var_nlevels   N Levels         3 #> 6       ARM        Placebo regressi…      contrasts  contrasts contr.tr… #> 7       ARM        Placebo regressi… contrasts_type  Contrast… treatment #> 8       ARM        Placebo regressi…  reference_row  referenc…      TRUE #> 9       ARM        Placebo regressi…          label  Level La…   Placebo #> 10      ARM        Placebo regressi…          n_obs     N Obs.        86 #> ℹ 33 more rows #> ℹ Use `print(n = ...)` to see more rows #> ℹ 1 more variable: fmt_fn"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_regression_basic.html","id":null,"dir":"Reference","previous_headings":"","what":"Basic Regression ARD — ard_regression_basic","title":"Basic Regression ARD — ard_regression_basic","text":"function takes regression model provides basic statistics ARD structure. default output simpler ard_regression(). function primarily matches regression terms underlying variable names levels. default arguments used ","code":"broom.helpers::tidy_plus_plus(   add_reference_rows = FALSE,   add_estimate_to_reference_rows = FALSE,   add_n = FALSE,   intercept = FALSE )"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_regression_basic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Basic Regression ARD — ard_regression_basic","text":"","code":"ard_regression_basic(   x,   tidy_fun = broom.helpers::tidy_with_broom_or_parameters,   stats_to_remove = c(\"term\", \"var_type\", \"var_label\", \"var_class\", \"label\",     \"contrasts_type\", \"contrasts\", \"var_nlevels\"),   ... )"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_regression_basic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Basic Regression ARD — ard_regression_basic","text":"x regression model object tidy_fun (function) tidier. Default broom.helpers::tidy_with_broom_or_parameters stats_to_remove (character) character vector statistic names remove. Default c(\"term\", \"var_type\", \"var_label\", \"var_class\", \"label\", \"contrasts_type\", \"contrasts\", \"var_nlevels\"). ... Arguments passed broom.helpers::tidy_plus_plus()","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_regression_basic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Basic Regression ARD — ard_regression_basic","text":"data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_regression_basic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Basic Regression ARD — ard_regression_basic","text":"","code":"lm(AGE ~ ARM, data = cards::ADSL) |>   ard_regression_basic() #> {cards} data frame: 12 x 7 #>    variable variable_level   context stat_name stat_label   stat #> 1       ARM      Xanomeli… regressi…  estimate  Coeffici… -0.828 #> 2       ARM      Xanomeli… regressi… std.error  Standard…  1.267 #> 3       ARM      Xanomeli… regressi… statistic  statistic -0.654 #> 4       ARM      Xanomeli… regressi…   p.value    p-value  0.514 #> 5       ARM      Xanomeli… regressi…  conf.low  CI Lower… -3.324 #> 6       ARM      Xanomeli… regressi… conf.high  CI Upper…  1.668 #> 7       ARM      Xanomeli… regressi…  estimate  Coeffici…  0.457 #> 8       ARM      Xanomeli… regressi… std.error  Standard…  1.267 #> 9       ARM      Xanomeli… regressi… statistic  statistic  0.361 #> 10      ARM      Xanomeli… regressi…   p.value    p-value  0.719 #> 11      ARM      Xanomeli… regressi…  conf.low  CI Lower… -2.039 #> 12      ARM      Xanomeli… regressi… conf.high  CI Upper…  2.953 #> ℹ 1 more variable: fmt_fn"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_smd_smd.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Standardized Mean Difference — ard_smd_smd","title":"ARD Standardized Mean Difference — ard_smd_smd","text":"Standardized mean difference calculated via smd::smd() na.rm = TRUE.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_smd_smd.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Standardized Mean Difference — ard_smd_smd","text":"","code":"ard_smd_smd(data, by, variables, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_smd_smd.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Standardized Mean Difference — ard_smd_smd","text":"data (data.frame/survey.design) data frame object class 'survey.design' (typically created survey::svydesign()). (tidy-select) column name compare . variables (tidy-select) column names compared. Independent tests computed variable. ... Arguments passed smd::smd std.error Logical indicator computing standard errors using compute_smd_var. Defaults FALSE. gref integer indicating level g use reference group. Defaults 1.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_smd_smd.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Standardized Mean Difference — ard_smd_smd","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_smd_smd.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Standardized Mean Difference — ard_smd_smd","text":"","code":"ard_smd_smd(cards::ADSL, by = ARM, variables = AGE, std.error = TRUE) #> {cards} data frame: 3 x 9 #>   group1 variable context stat_name stat_label          stat #> 1    ARM      AGE smd_smd  estimate  Standard… 0.101, -0.055 #> 2    ARM      AGE smd_smd std.error  Standard…  0.154, 0.153 #> 3    ARM      AGE smd_smd      gref  Integer …             1 #> ℹ 3 more variables: fmt_fn, warning, error ard_smd_smd(cards::ADSL, by = ARM, variables = AGEGR1, std.error = TRUE) #> {cards} data frame: 3 x 9 #>   group1 variable context stat_name stat_label         stat #> 1    ARM   AGEGR1 smd_smd  estimate  Standard… 0.351, 0.214 #> 2    ARM   AGEGR1 smd_smd std.error  Standard… 0.155, 0.154 #> 3    ARM   AGEGR1 smd_smd      gref  Integer …            1 #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_anova.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD ANOVA — ard_stats_anova","title":"ARD ANOVA — ard_stats_anova","text":"Prepare ANOVA results stats::anova() function. Users may pass pre-calculated stats::anova() object list formulas. latter case, models constructed using information passed models passed stats::anova().","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_anova.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD ANOVA — ard_stats_anova","text":"","code":"ard_stats_anova(x, ...)  # S3 method for anova ard_stats_anova(x, method_text = \"ANOVA results from `stats::anova()`\", ...)  # S3 method for data.frame ard_stats_anova(   x,   formulas,   method,   method.args = list(),   package = \"base\",   method_text = \"ANOVA results from `stats::anova()`\",   ... )"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_anova.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD ANOVA — ard_stats_anova","text":"x (anova data.frame) object class 'anova' created stats::anova() data frame ... dots future extensions must empty. method_text (string) string method used. Default \"ANOVA results stats::anova()\". provide option change stats::anova() can produce results many types models may warrant precise description. formulas (list) list formulas method (string) string naming function called, e.g. \"glm\". function belongs library attached, package name must specified package argument. method.args (named list) named list arguments passed fn. package (string) string package name temporarily loaded function specified method executed.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_anova.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD ANOVA — ard_stats_anova","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_anova.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"ARD ANOVA — ard_stats_anova","text":"list formulas supplied ard_stats_anova(), formulas along information arguments, used construct models pass models stats::anova(). models constructed using rlang::exec(), similar .call().   function executed withr::with_namespace(package), allows use ard_stats_anova(method) packages, e.g. package = 'lme4' must specified method = 'glmer'. See example .","code":"rlang::exec(.fn = method, formula = formula, data = data, !!!method.args)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_anova.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD ANOVA — ard_stats_anova","text":"","code":"anova(   lm(mpg ~ am, mtcars),   lm(mpg ~ am + hp, mtcars) ) |>   ard_stats_anova() #> {cards} data frame: 11 x 8 #>    variable   context   stat_name stat_label      stat fmt_fn #> 1   model_1 stats_an…        term       term  mpg ~ am   NULL #> 2   model_1 stats_an… df.residual  df for r…        30      1 #> 3   model_1 stats_an…         rss  Residual…   720.897      1 #> 4   model_2 stats_an…        term       term mpg ~ am…   NULL #> 5   model_2 stats_an… df.residual  df for r…        29      1 #> 6   model_2 stats_an…         rss  Residual…   245.439      1 #> 7   model_2 stats_an…          df  Degrees …         1      1 #> 8   model_2 stats_an…       sumsq  Sum of S…   475.457      1 #> 9   model_2 stats_an…   statistic  statistic    56.178      1 #> 10  model_2 stats_an…     p.value    p-value         0      1 #> 11  model_2 stats_an…      method     method ANOVA re…   NULL #> ℹ 2 more variables: warning, error  ard_stats_anova(   x = mtcars,   formulas = list(am ~ mpg, am ~ mpg + hp),   method = \"glm\",   method.args = list(family = binomial) ) #> {cards} data frame: 9 x 8 #>   variable   context         stat_name stat_label      stat fmt_fn #> 1  model_1 stats_an…              term       term  am ~ mpg   NULL #> 2  model_1 stats_an…       df.residual  df for r…        30      1 #> 3  model_1 stats_an… residual.deviance  residual…    29.675      1 #> 4  model_2 stats_an…              term       term am ~ mpg…   NULL #> 5  model_2 stats_an…       df.residual  df for r…        29      1 #> 6  model_2 stats_an… residual.deviance  residual…    19.233      1 #> 7  model_2 stats_an…                df  Degrees …         1      1 #> 8  model_2 stats_an…          deviance   deviance    10.443      1 #> 9  model_2 stats_an…            method     method ANOVA re…   NULL #> ℹ 2 more variables: warning, error  ard_stats_anova(   x = mtcars,   formulas = list(am ~ 1 + (1 | vs), am ~ mpg + (1 | vs)),   method = \"glmer\",   method.args = list(family = binomial),   package = \"lme4\" ) #> {cards} data frame: 16 x 8 #>    variable   context stat_name stat_label      stat   warning #> 1   model_1 stats_an…      term       term    MODEL1 failed t… #> 2   model_1 stats_an…      npar       npar         2 failed t… #> 3   model_1 stats_an…       AIC        AIC     47.23 failed t… #> 4   model_1 stats_an…       BIC        BIC    50.161 failed t… #> 5   model_1 stats_an…    logLik     logLik   -21.615 failed t… #> 6   model_1 stats_an…  deviance   deviance     43.23 failed t… #> 7   model_2 stats_an…      term       term    MODEL2 failed t… #> 8   model_2 stats_an…      npar       npar         3 failed t… #> 9   model_2 stats_an…       AIC        AIC     35.25 failed t… #> 10  model_2 stats_an…       BIC        BIC    39.647 failed t… #> 11  model_2 stats_an…    logLik     logLik   -14.625 failed t… #> 12  model_2 stats_an…  deviance   deviance     29.25 failed t… #> 13  model_2 stats_an… statistic  statistic    13.979 failed t… #> 14  model_2 stats_an…        df  Degrees …         1 failed t… #> 15  model_2 stats_an…   p.value    p-value         0 failed t… #> 16  model_2 stats_an…    method     method ANOVA re… failed t… #> ℹ 2 more variables: fmt_fn, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_aov.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD ANOVA — ard_stats_aov","title":"ARD ANOVA — ard_stats_aov","text":"Analysis results data Analysis Variance. Calculated stats::aov()","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_aov.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD ANOVA — ard_stats_aov","text":"","code":"ard_stats_aov(formula, data, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_aov.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD ANOVA — ard_stats_aov","text":"formula formula specifying model. data data frame variables specified     formula found. missing, variables searched     standard way. ... arguments passed stats::aov(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_aov.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD ANOVA — ard_stats_aov","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_aov.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD ANOVA — ard_stats_aov","text":"","code":"ard_stats_aov(AGE ~ ARM, data = cards::ADSL) #> {cards} data frame: 5 x 7 #>   variable   context stat_name stat_label   stat error #> 1      ARM stats_aov     sumsq  Sum of S… 71.386       #> 2      ARM stats_aov        df  Degrees …      2       #> 3      ARM stats_aov    meansq  Mean of … 35.693       #> 4      ARM stats_aov statistic  Statistic  0.523       #> 5      ARM stats_aov   p.value    p-value  0.593       #> ℹ 1 more variable: warning"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_chisq_test.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Chi-squared Test — ard_stats_chisq_test","title":"ARD Chi-squared Test — ard_stats_chisq_test","text":"Analysis results data Pearson's Chi-squared Test. Calculated chisq.test(x = data[[variable]], y = data[[]], ...)","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_chisq_test.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Chi-squared Test — ard_stats_chisq_test","text":"","code":"ard_stats_chisq_test(data, by, variables, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_chisq_test.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Chi-squared Test — ard_stats_chisq_test","text":"data (data.frame) data frame. (tidy-select) column name compare . variables (tidy-select) column names compared. Independent tests computed variable. ... additional arguments passed chisq.test(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_chisq_test.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Chi-squared Test — ard_stats_chisq_test","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_chisq_test.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Chi-squared Test — ard_stats_chisq_test","text":"","code":"cards::ADSL |>   ard_stats_chisq_test(by = \"ARM\", variables = \"AGEGR1\") #> {cards} data frame: 9 x 9 #>   group1 variable   context        stat_name stat_label #> 1    ARM   AGEGR1 stats_ch…        statistic  X-square… #> 2    ARM   AGEGR1 stats_ch…          p.value    p-value #> 3    ARM   AGEGR1 stats_ch…        parameter  Degrees … #> 4    ARM   AGEGR1 stats_ch…           method     method #> 5    ARM   AGEGR1 stats_ch…          correct    correct #> 6    ARM   AGEGR1 stats_ch…                p          p #> 7    ARM   AGEGR1 stats_ch…        rescale.p  rescale.p #> 8    ARM   AGEGR1 stats_ch… simulate.p.value  simulate… #> 9    ARM   AGEGR1 stats_ch…                B          B #>                          stat #> 1                       6.852 #> 2                       0.144 #> 3                           4 #> 4                   Pearson'… #> 5                        TRUE #> 6 rep, 1/length(x), length(x) #> 7                       FALSE #> 8                       FALSE #> 9                        2000 #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_fisher_test.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Fisher's Exact Test — ard_stats_fisher_test","title":"ARD Fisher's Exact Test — ard_stats_fisher_test","text":"Analysis results data Fisher's Exact Test. Calculated fisher.test(x = data[[variable]], y = data[[]], ...)","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_fisher_test.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Fisher's Exact Test — ard_stats_fisher_test","text":"","code":"ard_stats_fisher_test(data, by, variables, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_fisher_test.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Fisher's Exact Test — ard_stats_fisher_test","text":"data (data.frame) data frame. (tidy-select) column name compare variables (tidy-select) column names compared. Independent tests computed variable. ... additional arguments passed fisher.test(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_fisher_test.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Fisher's Exact Test — ard_stats_fisher_test","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_fisher_test.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Fisher's Exact Test — ard_stats_fisher_test","text":"","code":"cards::ADSL[1:30, ] |>   ard_stats_fisher_test(by = \"ARM\", variables = \"AGEGR1\") #> {cards} data frame: 12 x 9 #>    group1 variable   context        stat_name stat_label        stat #> 1     ARM   AGEGR1 stats_fi…          p.value    p-value       0.089 #> 2     ARM   AGEGR1 stats_fi…           method     method   Fisher's… #> 3     ARM   AGEGR1 stats_fi…      alternative  alternat…   two.sided #> 4     ARM   AGEGR1 stats_fi…        workspace  workspace       2e+05 #> 5     ARM   AGEGR1 stats_fi…           hybrid     hybrid       FALSE #> 6     ARM   AGEGR1 stats_fi…       hybridPars  hybridPa… c, 5, 80, 1 #> 7     ARM   AGEGR1 stats_fi…          control    control        list #> 8     ARM   AGEGR1 stats_fi…               or         or           1 #> 9     ARM   AGEGR1 stats_fi…         conf.int   conf.int        TRUE #> 10    ARM   AGEGR1 stats_fi…       conf.level  conf.lev…        0.95 #> 11    ARM   AGEGR1 stats_fi… simulate.p.value  simulate…       FALSE #> 12    ARM   AGEGR1 stats_fi…                B          B        2000 #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_kruskal_test.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Kruskal-Wallis Test — ard_stats_kruskal_test","title":"ARD Kruskal-Wallis Test — ard_stats_kruskal_test","text":"Analysis results data Kruskal-Wallis Rank Sum Test. Calculated kruskal.test(data[[variable]], data[[]], ...)","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_kruskal_test.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Kruskal-Wallis Test — ard_stats_kruskal_test","text":"","code":"ard_stats_kruskal_test(data, by, variables)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_kruskal_test.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Kruskal-Wallis Test — ard_stats_kruskal_test","text":"data (data.frame) data frame. (tidy-select) column name compare . variables (tidy-select) column names compared. Independent tests computed variable.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_kruskal_test.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Kruskal-Wallis Test — ard_stats_kruskal_test","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_kruskal_test.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Kruskal-Wallis Test — ard_stats_kruskal_test","text":"","code":"cards::ADSL |>   ard_stats_kruskal_test(by = \"ARM\", variables = \"AGE\") #> {cards} data frame: 4 x 9 #>   group1 variable   context stat_name stat_label      stat #> 1    ARM      AGE stats_kr… statistic  Kruskal-…     1.635 #> 2    ARM      AGE stats_kr…   p.value    p-value     0.442 #> 3    ARM      AGE stats_kr… parameter  Degrees …         2 #> 4    ARM      AGE stats_kr…    method     method Kruskal-… #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_mcnemar_test.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD McNemar's Test — ard_stats_mcnemar_test","title":"ARD McNemar's Test — ard_stats_mcnemar_test","text":"Analysis results data McNemar's statistical test. two functions depending structure data. ard_stats_mcnemar_test() structure expected stats::mcnemar.test() ard_stats_mcnemar_test_long() one row per ID per group","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_mcnemar_test.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD McNemar's Test — ard_stats_mcnemar_test","text":"","code":"ard_stats_mcnemar_test(data, by, variables, ...)  ard_stats_mcnemar_test_long(data, by, variables, id, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_mcnemar_test.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD McNemar's Test — ard_stats_mcnemar_test","text":"data (data.frame) data frame. See details. (tidy-select) column name compare . variables (tidy-select) column names compared. Independent tests computed variable. ... arguments passed stats::mcnemar.test(...) id (tidy-select) column name subject participant ID","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_mcnemar_test.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD McNemar's Test — ard_stats_mcnemar_test","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_mcnemar_test.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"ARD McNemar's Test — ard_stats_mcnemar_test","text":"ard_stats_mcnemar_test() function, data expected one row per subject. data passed stats::mcnemar.test(x = data[[variable]], y = data[[]], ...). Please use table(x = data[[variable]], y = data[[]]) check contingency table.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_mcnemar_test.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD McNemar's Test — ard_stats_mcnemar_test","text":"","code":"cards::ADSL |>   ard_stats_mcnemar_test(by = \"SEX\", variables = \"EFFFL\") #> {cards} data frame: 5 x 9 #>   group1 variable   context stat_name stat_label      stat #> 1    SEX    EFFFL stats_mc… statistic  X-square…    111.91 #> 2    SEX    EFFFL stats_mc…   p.value    p-value         0 #> 3    SEX    EFFFL stats_mc… parameter  Degrees …         1 #> 4    SEX    EFFFL stats_mc…    method     method McNemar'… #> 5    SEX    EFFFL stats_mc…   correct    correct      TRUE #> ℹ 3 more variables: fmt_fn, warning, error  set.seed(1234) cards::ADSL[c(\"USUBJID\", \"TRT01P\")] |>   dplyr::mutate(TYPE = \"PLANNED\") |>   dplyr::rename(TRT01 = TRT01P) %>%   dplyr::bind_rows(dplyr::mutate(., TYPE = \"ACTUAL\", TRT01 = sample(TRT01))) |>   ard_stats_mcnemar_test_long(     by = TYPE,     variable = TRT01,     id = USUBJID   ) #> {cards} data frame: 5 x 9 #>   group1 variable   context stat_name stat_label      stat #> 1   TYPE    TRT01 stats_mc… statistic  X-square…     1.353 #> 2   TYPE    TRT01 stats_mc…   p.value    p-value     0.717 #> 3   TYPE    TRT01 stats_mc… parameter  Degrees …         3 #> 4   TYPE    TRT01 stats_mc…    method     method McNemar'… #> 5   TYPE    TRT01 stats_mc…   correct    correct      TRUE #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_mood_test.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Mood Test — ard_stats_mood_test","title":"ARD Mood Test — ard_stats_mood_test","text":"Analysis results data Mood two sample test scale. Note confused Brown-Mood test medians.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_mood_test.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Mood Test — ard_stats_mood_test","text":"","code":"ard_stats_mood_test(data, by, variables, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_mood_test.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Mood Test — ard_stats_mood_test","text":"data (data.frame) data frame. See details. (tidy-select) column name compare . variables (tidy-select) column name compared. Independent tests run variable. ... arguments passed mood.test(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_mood_test.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Mood Test — ard_stats_mood_test","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_mood_test.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"ARD Mood Test — ard_stats_mood_test","text":"ard_stats_mood_test() function, data expected one row per subject. data passed mood.test(data[[variable]] ~ data[[]], ...).","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_mood_test.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Mood Test — ard_stats_mood_test","text":"","code":"cards::ADSL |>   ard_stats_mood_test(by = \"SEX\", variables = \"AGE\") #> {cards} data frame: 4 x 9 #>   group1 variable   context   stat_name stat_label      stat #> 1    SEX      AGE stats_mo…   statistic  Z-Statis…     0.129 #> 2    SEX      AGE stats_mo…     p.value    p-value     0.897 #> 3    SEX      AGE stats_mo…      method     method Mood two… #> 4    SEX      AGE stats_mo… alternative  Alternat… two.sided #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_oneway_test.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD One-way Test — ard_stats_oneway_test","title":"ARD One-way Test — ard_stats_oneway_test","text":"Analysis results data Testing Equal Means One-Way Layout. calculated oneway.test()","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_oneway_test.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD One-way Test — ard_stats_oneway_test","text":"","code":"ard_stats_oneway_test(formula, data, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_oneway_test.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD One-way Test — ard_stats_oneway_test","text":"formula formula form lhs ~ rhs lhs     gives sample values rhs corresponding groups. data optional matrix data frame (similar: see     model.frame) containing variables     formula formula.  default variables taken     environment(formula). ... additional arguments passed oneway.test(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_oneway_test.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD One-way Test — ard_stats_oneway_test","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_oneway_test.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD One-way Test — ard_stats_oneway_test","text":"","code":"ard_stats_oneway_test(AGE ~ ARM, data = cards::ADSL) #> {cards} data frame: 6 x 7 #>     context stat_name stat_label      stat fmt_fn error #> 1 stats_on…    num.df  Degrees …         2      1       #> 2 stats_on…    den.df  Denomina…   167.237      1       #> 3 stats_on… statistic  F Statis…     0.547      1       #> 4 stats_on…   p.value    p-value      0.58      1       #> 5 stats_on…    method     Method One-way …   NULL       #> 6 stats_on… var.equal  var.equal     FALSE   NULL       #> ℹ 1 more variable: warning"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_prop_test.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD 2-sample proportion test — ard_stats_prop_test","title":"ARD 2-sample proportion test — ard_stats_prop_test","text":"Analysis results data 2-sample test proportions using stats::prop.test().","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_prop_test.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD 2-sample proportion test — ard_stats_prop_test","text":"","code":"ard_stats_prop_test(data, by, variables, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_prop_test.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD 2-sample proportion test — ard_stats_prop_test","text":"data (data.frame) data frame. (tidy-select) column name compare variables (tidy-select) column names compared. Must binary column coded TRUE/FALSE 1/0. Independent tests computed variable. ... arguments passed prop.test(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_prop_test.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD 2-sample proportion test — ard_stats_prop_test","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_prop_test.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD 2-sample proportion test — ard_stats_prop_test","text":"","code":"mtcars |>   ard_stats_prop_test(by = vs, variables = am) #> {cards} data frame: 13 x 9 #>    group1 variable   context   stat_name stat_label      stat #> 1      vs       am stats_pr…    estimate  Rate Dif…    -0.167 #> 2      vs       am stats_pr…   estimate1  Group 1 …     0.333 #> 3      vs       am stats_pr…   estimate2  Group 2 …       0.5 #> 4      vs       am stats_pr…   statistic  X-square…     0.348 #> 5      vs       am stats_pr…     p.value    p-value     0.556 #> 6      vs       am stats_pr…   parameter  Degrees …         1 #> 7      vs       am stats_pr…    conf.low  CI Lower…    -0.571 #> 8      vs       am stats_pr…   conf.high  CI Upper…     0.237 #> 9      vs       am stats_pr…      method     method 2-sample… #> 10     vs       am stats_pr… alternative  alternat… two.sided #> 11     vs       am stats_pr…           p          p           #> 12     vs       am stats_pr…  conf.level  CI Confi…      0.95 #> 13     vs       am stats_pr…     correct  Yates' c…      TRUE #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_t_test.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD t-test — ard_stats_t_test","title":"ARD t-test — ard_stats_t_test","text":"Analysis results data paired non-paired t-tests.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_t_test.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD t-test — ard_stats_t_test","text":"","code":"ard_stats_t_test(data, variables, by = NULL, ...)  ard_stats_paired_t_test(data, by, variables, id, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_t_test.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD t-test — ard_stats_t_test","text":"data (data.frame) data frame. See details. variables (tidy-select) column names compared. Independent t-tests computed variable. (tidy-select) optional column name compare . ... arguments passed t.test(...) id (tidy-select) column name subject participant ID","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_t_test.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD t-test — ard_stats_t_test","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_t_test.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"ARD t-test — ard_stats_t_test","text":"ard_stats_t_test() function, data expected one row per subject. data passed t.test(data[[variable]] ~ data[[]], paired = FALSE, ...). ard_stats_paired_t_test() function, data expected one row per subject per level. t-test calculated, data reshaped wide format one row per subject. data passed t.test(x = data_wide[[<level 1>]], y = data_wide[[<level 2>]], paired = TRUE, ...).","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_t_test.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD t-test — ard_stats_t_test","text":"","code":"cards::ADSL |>   dplyr::filter(ARM %in% c(\"Placebo\", \"Xanomeline High Dose\")) |>   ard_stats_t_test(by = ARM, variables = c(AGE, BMIBL)) #> {cards} data frame: 28 x 9 #>    group1 variable   context   stat_name stat_label      stat #> 1     ARM      AGE stats_t_…    estimate  Mean Dif…     0.828 #> 2     ARM      AGE stats_t_…   estimate1  Group 1 …    75.209 #> 3     ARM      AGE stats_t_…   estimate2  Group 2 …    74.381 #> 4     ARM      AGE stats_t_…   statistic  t Statis…     0.655 #> 5     ARM      AGE stats_t_…     p.value    p-value     0.513 #> 6     ARM      AGE stats_t_…   parameter  Degrees …   167.362 #> 7     ARM      AGE stats_t_…    conf.low  CI Lower…    -1.668 #> 8     ARM      AGE stats_t_…   conf.high  CI Upper…     3.324 #> 9     ARM      AGE stats_t_…      method     method Welch Tw… #> 10    ARM      AGE stats_t_… alternative  alternat… two.sided #> ℹ 18 more rows #> ℹ Use `print(n = ...)` to see more rows #> ℹ 3 more variables: fmt_fn, warning, error  # constructing a paired data set, # where patients receive both treatments cards::ADSL[c(\"ARM\", \"AGE\")] |>   dplyr::filter(ARM %in% c(\"Placebo\", \"Xanomeline High Dose\")) |>   dplyr::mutate(.by = ARM, USUBJID = dplyr::row_number()) |>   dplyr::arrange(USUBJID, ARM) |>   ard_stats_paired_t_test(by = ARM, variables = AGE, id = USUBJID) #> {cards} data frame: 12 x 9 #>    group1 variable   context   stat_name stat_label      stat #> 1     ARM      AGE stats_t_…    estimate  Mean Dif…     0.798 #> 2     ARM      AGE stats_t_…   statistic  t Statis…     0.628 #> 3     ARM      AGE stats_t_…     p.value    p-value     0.531 #> 4     ARM      AGE stats_t_…   parameter  Degrees …        83 #> 5     ARM      AGE stats_t_…    conf.low  CI Lower…    -1.727 #> 6     ARM      AGE stats_t_…   conf.high  CI Upper…     3.322 #> 7     ARM      AGE stats_t_…      method     method Paired t… #> 8     ARM      AGE stats_t_… alternative  alternat… two.sided #> 9     ARM      AGE stats_t_…          mu    H0 Mean         0 #> 10    ARM      AGE stats_t_…      paired  Paired t…      TRUE #> 11    ARM      AGE stats_t_…   var.equal  Equal Va…     FALSE #> 12    ARM      AGE stats_t_…  conf.level  CI Confi…      0.95 #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_wilcox_test.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Wilcoxon Rank-Sum Test — ard_stats_wilcox_test","title":"ARD Wilcoxon Rank-Sum Test — ard_stats_wilcox_test","text":"Analysis results data paired non-paired Wilcoxon Rank-Sum tests.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_wilcox_test.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Wilcoxon Rank-Sum Test — ard_stats_wilcox_test","text":"","code":"ard_stats_wilcox_test(data, variables, by = NULL, ...)  ard_stats_paired_wilcox_test(data, by, variables, id, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_wilcox_test.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Wilcoxon Rank-Sum Test — ard_stats_wilcox_test","text":"data (data.frame) data frame. See details. variables (tidy-select) column names compared. Independent tests computed variable. (tidy-select) optional column name compare . ... arguments passed wilcox.test(...) id (tidy-select) column name subject participant ID.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_wilcox_test.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Wilcoxon Rank-Sum Test — ard_stats_wilcox_test","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_wilcox_test.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"ARD Wilcoxon Rank-Sum Test — ard_stats_wilcox_test","text":"ard_stats_wilcox_test() function, data expected one row per subject. data passed wilcox.test(data[[variable]] ~ data[[]], paired = FALSE, ...). ard_stats_paired_wilcox_test() function, data expected one row per subject per level. test calculated, data reshaped wide format one row per subject. data passed wilcox.test(x = data_wide[[<level 1>]], y = data_wide[[<level 2>]], paired = TRUE, ...).","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_stats_wilcox_test.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Wilcoxon Rank-Sum Test — ard_stats_wilcox_test","text":"","code":"cards::ADSL |>   dplyr::filter(ARM %in% c(\"Placebo\", \"Xanomeline High Dose\")) |>   ard_stats_wilcox_test(by = \"ARM\", variables = \"AGE\") #> {cards} data frame: 12 x 9 #>    group1 variable   context   stat_name stat_label      stat #> 1     ARM      AGE stats_wi…   statistic  X-square…    3862.5 #> 2     ARM      AGE stats_wi…     p.value    p-value     0.435 #> 3     ARM      AGE stats_wi…      method     method Wilcoxon… #> 4     ARM      AGE stats_wi… alternative  alternat… two.sided #> 5     ARM      AGE stats_wi…          mu         mu         0 #> 6     ARM      AGE stats_wi…      paired  Paired t…     FALSE #> 7     ARM      AGE stats_wi…       exact      exact           #> 8     ARM      AGE stats_wi…     correct    correct      TRUE #> 9     ARM      AGE stats_wi…    conf.int   conf.int     FALSE #> 10    ARM      AGE stats_wi…  conf.level  CI Confi…      0.95 #> 11    ARM      AGE stats_wi…    tol.root   tol.root         0 #> 12    ARM      AGE stats_wi… digits.rank  digits.r…       Inf #> ℹ 3 more variables: fmt_fn, warning, error  # constructing a paired data set, # where patients receive both treatments cards::ADSL[c(\"ARM\", \"AGE\")] |>   dplyr::filter(ARM %in% c(\"Placebo\", \"Xanomeline High Dose\")) |>   dplyr::mutate(.by = ARM, USUBJID = dplyr::row_number()) |>   dplyr::arrange(USUBJID, ARM) |>   ard_stats_paired_wilcox_test(by = ARM, variables = AGE, id = USUBJID) #> {cards} data frame: 12 x 9 #>    group1 variable   context   stat_name stat_label      stat #> 1     ARM      AGE stats_wi…   statistic  X-square…      1754 #> 2     ARM      AGE stats_wi…     p.value    p-value     0.522 #> 3     ARM      AGE stats_wi…      method     method Wilcoxon… #> 4     ARM      AGE stats_wi… alternative  alternat… two.sided #> 5     ARM      AGE stats_wi…          mu         mu         0 #> 6     ARM      AGE stats_wi…      paired  Paired t…      TRUE #> 7     ARM      AGE stats_wi…       exact      exact           #> 8     ARM      AGE stats_wi…     correct    correct      TRUE #> 9     ARM      AGE stats_wi…    conf.int   conf.int     FALSE #> 10    ARM      AGE stats_wi…  conf.level  CI Confi…      0.95 #> 11    ARM      AGE stats_wi…    tol.root   tol.root         0 #> 12    ARM      AGE stats_wi… digits.rank  digits.r…       Inf #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survey_svychisq.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Survey Chi-Square Test — ard_survey_svychisq","title":"ARD Survey Chi-Square Test — ard_survey_svychisq","text":"Analysis results data survey Chi-Square test using survey::svychisq(). two-way comparisons supported.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survey_svychisq.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Survey Chi-Square Test — ard_survey_svychisq","text":"","code":"ard_survey_svychisq(data, by, variables, statistic = \"F\", ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survey_svychisq.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Survey Chi-Square Test — ard_survey_svychisq","text":"data (survey.design) survey design object often created survey package (tidy-select) column name compare . variables (tidy-select) column names compared. Independent tests computed variable. statistic (character) statistic used estimate Chisq p-value. Default Rao-Scott second-order correction (\"F\"). See survey::svychisq available statistics options. ... arguments passed survey::svychisq().","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survey_svychisq.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Survey Chi-Square Test — ard_survey_svychisq","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survey_svychisq.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Survey Chi-Square Test — ard_survey_svychisq","text":"","code":"data(api, package = \"survey\") dclus1 <- survey::svydesign(id = ~dnum, weights = ~pw, data = apiclus1, fpc = ~fpc)  ard_survey_svychisq(dclus1, variables = sch.wide, by = comp.imp, statistic = \"F\") #> {cards} data frame: 5 x 9 #>     group1 variable   context stat_name stat_label      stat #> 1 comp.imp sch.wide survey_s…       ndf  Nominato…         1 #> 2 comp.imp sch.wide survey_s…       ddf  Denomina…        14 #> 3 comp.imp sch.wide survey_s… statistic  Statistic   236.895 #> 4 comp.imp sch.wide survey_s…   p.value    p-value         0 #> 5 comp.imp sch.wide survey_s…    method     method Pearson'… #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survey_svycontinuous.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Continuous Survey Statistics — ard_survey_svycontinuous","title":"ARD Continuous Survey Statistics — ard_survey_svycontinuous","text":"Returns ARD weighted statistics using {survey} package.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survey_svycontinuous.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Continuous Survey Statistics — ard_survey_svycontinuous","text":"","code":"ard_survey_svycontinuous(   data,   variables,   by = NULL,   statistic = everything() ~ c(\"median\", \"p25\", \"p75\"),   fmt_fn = NULL,   stat_label = NULL )"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survey_svycontinuous.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Continuous Survey Statistics — ard_survey_svycontinuous","text":"data (survey.design) design object often created survey::svydesign(). variables (tidy-select) columns include summaries. Default everything(). (tidy-select) results calculated combinations columns specified, including unobserved combinations unobserved factor levels. statistic (formula-list-selector) named list, list formulas, single formula list element character vector statistic names include. See options. fmt_fn (formula-list-selector) named list, list formulas, single formula list element named list functions (RHS formula), e.g. list(mpg = list(mean = \\(x) round(x, digits = 2) |> .character)). stat_label (formula-list-selector) named list, list formulas, single formula list element either named list list formulas defining statistic labels, e.g. everything() ~ list(mean = \"Mean\", sd = \"SD\") everything() ~ list(mean ~ \"Mean\", sd ~ \"SD\").","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survey_svycontinuous.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Continuous Survey Statistics — ard_survey_svycontinuous","text":"ARD data frame class 'card'","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survey_svycontinuous.html","id":"statistic-argument","dir":"Reference","previous_headings":"","what":"statistic argument","title":"ARD Continuous Survey Statistics — ard_survey_svycontinuous","text":"following statistics available: 'mean', 'median', 'min', 'max', 'sum', 'var', 'sd', 'mean.std.error', 'deff', 'p##', 'p##' percentiles ## integer 0 100.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survey_svycontinuous.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Continuous Survey Statistics — ard_survey_svycontinuous","text":"","code":"data(api, package = \"survey\") dclus1 <- survey::svydesign(id = ~dnum, weights = ~pw, data = apiclus1, fpc = ~fpc)  ard_survey_svycontinuous(   data = dclus1,   variables = api00,   by = stype ) #> {cards} data frame: 9 x 10 #>   group1 group1_level variable stat_name stat_label stat #> 1  stype            E    api00    median     Median  652 #> 2  stype            H    api00    median     Median  608 #> 3  stype            M    api00    median     Median  642 #> 4  stype            E    api00       p25  25% Perc…  553 #> 5  stype            H    api00       p25  25% Perc…  529 #> 6  stype            M    api00       p25  25% Perc…  547 #> 7  stype            E    api00       p75  75% Perc…  729 #> 8  stype            H    api00       p75  75% Perc…  703 #> 9  stype            M    api00       p75  75% Perc…  699 #> ℹ 4 more variables: context, fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survey_svyranktest.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Survey rank test — ard_survey_svyranktest","title":"ARD Survey rank test — ard_survey_svyranktest","text":"Analysis results data survey wilcox test using survey::svyranktest().","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survey_svyranktest.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Survey rank test — ard_survey_svyranktest","text":"","code":"ard_survey_svyranktest(data, by, variables, test, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survey_svyranktest.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Survey rank test — ard_survey_svyranktest","text":"data (survey.design) survey design object often created survey::svydesign() (tidy-select) column name compare variables (tidy-select) column names compared. Independent tests run variable. test (string) string denote rank test use: \"wilcoxon\", \"vanderWaerden\", \"median\", \"KruskalWallis\" ... arguments passed survey::svyranktest()","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survey_svyranktest.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Survey rank test — ard_survey_svyranktest","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survey_svyranktest.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Survey rank test — ard_survey_svyranktest","text":"","code":"data(api, package = \"survey\") dclus2 <- survey::svydesign(id = ~ dnum + snum, fpc = ~ fpc1 + fpc2, data = apiclus2)  ard_survey_svyranktest(dclus2, variables = enroll, by = comp.imp, test = \"wilcoxon\") #> {cards} data frame: 6 x 9 #>     group1 variable   context   stat_name stat_label      stat #> 1 comp.imp   enroll survey_s…    estimate  Median o…    -0.106 #> 2 comp.imp   enroll survey_s…   statistic  Statistic    -1.719 #> 3 comp.imp   enroll survey_s…     p.value    p-value     0.094 #> 4 comp.imp   enroll survey_s…   parameter  Degrees …        36 #> 5 comp.imp   enroll survey_s…      method     method Design-b… #> 6 comp.imp   enroll survey_s… alternative  Alternat… two.sided #> ℹ 3 more variables: fmt_fn, warning, error ard_survey_svyranktest(dclus2, variables = enroll, by = comp.imp, test = \"vanderWaerden\") #> {cards} data frame: 6 x 9 #>     group1 variable   context   stat_name stat_label      stat #> 1 comp.imp   enroll survey_s…    estimate  Median o…    -0.379 #> 2 comp.imp   enroll survey_s…   statistic  Statistic    -1.584 #> 3 comp.imp   enroll survey_s…     p.value    p-value     0.122 #> 4 comp.imp   enroll survey_s…   parameter  Degrees …        36 #> 5 comp.imp   enroll survey_s…      method     method Design-b… #> 6 comp.imp   enroll survey_s… alternative  Alternat… two.sided #> ℹ 3 more variables: fmt_fn, warning, error ard_survey_svyranktest(dclus2, variables = enroll, by = comp.imp, test = \"median\") #> {cards} data frame: 6 x 9 #>     group1 variable   context   stat_name stat_label      stat #> 1 comp.imp   enroll survey_s…    estimate  Median o…    -0.124 #> 2 comp.imp   enroll survey_s…   statistic  Statistic    -0.914 #> 3 comp.imp   enroll survey_s…     p.value    p-value     0.367 #> 4 comp.imp   enroll survey_s…   parameter  Degrees …        36 #> 5 comp.imp   enroll survey_s…      method     method Design-b… #> 6 comp.imp   enroll survey_s… alternative  Alternat… two.sided #> ℹ 3 more variables: fmt_fn, warning, error ard_survey_svyranktest(dclus2, variables = enroll, by = comp.imp, test = \"KruskalWallis\") #> {cards} data frame: 6 x 9 #>     group1 variable   context   stat_name stat_label      stat #> 1 comp.imp   enroll survey_s…    estimate  Median o…    -0.106 #> 2 comp.imp   enroll survey_s…   statistic  Statistic    -1.719 #> 3 comp.imp   enroll survey_s…     p.value    p-value     0.094 #> 4 comp.imp   enroll survey_s…   parameter  Degrees …        36 #> 5 comp.imp   enroll survey_s…      method     method Design-b… #> 6 comp.imp   enroll survey_s… alternative  Alternat… two.sided #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survey_svyttest.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Survey t-test — ard_survey_svyttest","title":"ARD Survey t-test — ard_survey_svyttest","text":"Analysis results data survey t-test using survey::svyttest().","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survey_svyttest.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Survey t-test — ard_survey_svyttest","text":"","code":"ard_survey_svyttest(data, by, variables, conf.level = 0.95, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survey_svyttest.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Survey t-test — ard_survey_svyttest","text":"data (survey.design) survey design object often created survey::svydesign() (tidy-select) column name compare variables (tidy-select) column names compared. Independent tests run variable. conf.level (double) confidence level returned confidence interval. Must c(0, 1). Default 0.95 ... arguments passed survey::svyttest()","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survey_svyttest.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Survey t-test — ard_survey_svyttest","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survey_svyttest.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Survey t-test — ard_survey_svyttest","text":"","code":"data(api, package = \"survey\") dclus2 <- survey::svydesign(id = ~ dnum + snum, fpc = ~ fpc1 + fpc2, data = apiclus2)  ard_survey_svyttest(dclus2, variables = enroll, by = comp.imp, conf.level = 0.9) #> {cards} data frame: 9 x 9 #>     group1 variable   context   stat_name stat_label      stat #> 1 comp.imp   enroll survey_s…    estimate       Mean  -225.737 #> 2 comp.imp   enroll survey_s…   statistic  t Statis…    -2.888 #> 3 comp.imp   enroll survey_s…     p.value    p-value     0.007 #> 4 comp.imp   enroll survey_s…   parameter  Degrees …        36 #> 5 comp.imp   enroll survey_s…      method     method Design-b… #> 6 comp.imp   enroll survey_s… alternative  alternat… two.sided #> 7 comp.imp   enroll survey_s…    conf.low  CI Lower…   -357.69 #> 8 comp.imp   enroll survey_s…   conf.high  CI Upper…   -93.784 #> 9 comp.imp   enroll survey_s…  conf.level  CI Confi…       0.9 #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survival_survdiff.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD for Difference in Survival — ard_survival_survdiff","title":"ARD for Difference in Survival — ard_survival_survdiff","text":"Analysis results data comparison survival using survival::survdiff().","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survival_survdiff.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD for Difference in Survival — ard_survival_survdiff","text":"","code":"ard_survival_survdiff(formula, data, rho = 0, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survival_survdiff.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD for Difference in Survival — ard_survival_survdiff","text":"formula (formula) formula data (data.frame) data frame rho (scalar numeric) numeric scalar passed survival::survdiff(rho). Default rho=0. ... additional arguments passed survival::survdiff()","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survival_survdiff.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD for Difference in Survival — ard_survival_survdiff","text":"ARD data frame class 'card'","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survival_survdiff.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD for Difference in Survival — ard_survival_survdiff","text":"","code":"library(survival) library(ggsurvfit) #> Loading required package: ggplot2  ard_survival_survdiff(Surv_CNSR(AVAL, CNSR) ~ TRTA, data = cards::ADTTE) #> {cards} data frame: 4 x 8 #>   variable   context stat_name stat_label      stat fmt_fn #> 1     TRTA survival… statistic  X^2 Stat…     60.27      1 #> 2     TRTA survival…        df  Degrees …         2      1 #> 3     TRTA survival…   p.value    p-value         0      1 #> 4     TRTA survival…    method     method Log-rank…   NULL #> ℹ 2 more variables: warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survival_survfit.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Survival Estimates — ard_survival_survfit","title":"ARD Survival Estimates — ard_survival_survfit","text":"Analysis results data survival quantiles x-year survival estimates, extracted survival::survfit() model.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survival_survfit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Survival Estimates — ard_survival_survfit","text":"","code":"ard_survival_survfit(x, times = NULL, probs = NULL, type = NULL)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survival_survfit.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Survival Estimates — ard_survival_survfit","text":"x (survival::survfit()) survival::survfit() object. See details. times (numeric) vector times return survival probabilities. probs (numeric) vector probabilities values (0,1) specifying survival quantiles return. type (string NULL) type statistic report. Available Kaplan-Meier time estimates , otherwise type ignored. Default NULL. Must one following:","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survival_survfit.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Survival Estimates — ard_survival_survfit","text":"ARD data frame class 'card'","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survival_survfit.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"ARD Survival Estimates — ard_survival_survfit","text":"one either times probs parameters can specified. Times provided using scale time variable used fit provided survival fit model.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/ard_survival_survfit.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Survival Estimates — ard_survival_survfit","text":"","code":"library(survival) library(ggsurvfit)  survfit(Surv_CNSR(AVAL, CNSR) ~ TRTA, cards::ADTTE) |>   ard_survival_survfit(times = c(60, 180)) #> {cards} data frame: 18 x 11 #>    group1 group1_level variable variable_level stat_name stat_label  stat #> 1    TRTA      Placebo     time             60  estimate  Survival… 0.768 #> 2    TRTA      Placebo     time             60 conf.high  CI Upper… 0.866 #> 3    TRTA      Placebo     time             60  conf.low  CI Lower… 0.682 #> 4    TRTA      Placebo     time            180  estimate  Survival… 0.626 #> 5    TRTA      Placebo     time            180 conf.high  CI Upper… 0.746 #> 6    TRTA      Placebo     time            180  conf.low  CI Lower… 0.526 #> 7    TRTA    Xanomeli…     time             60  estimate  Survival… 0.243 #> 8    TRTA    Xanomeli…     time             60 conf.high  CI Upper… 0.373 #> 9    TRTA    Xanomeli…     time             60  conf.low  CI Lower… 0.158 #> 10   TRTA    Xanomeli…     time            180  estimate  Survival… 0.092 #> 11   TRTA    Xanomeli…     time            180 conf.high  CI Upper… 0.221 #> 12   TRTA    Xanomeli…     time            180  conf.low  CI Lower… 0.038 #> 13   TRTA    Xanomeli…     time             60  estimate  Survival… 0.311 #> 14   TRTA    Xanomeli…     time             60 conf.high  CI Upper… 0.441 #> 15   TRTA    Xanomeli…     time             60  conf.low  CI Lower… 0.219 #> 16   TRTA    Xanomeli…     time            180  estimate  Survival… 0.126 #> 17   TRTA    Xanomeli…     time            180 conf.high  CI Upper… 0.249 #> 18   TRTA    Xanomeli…     time            180  conf.low  CI Lower… 0.064 #> ℹ 4 more variables: context, fmt_fn, warning, error  survfit(Surv_CNSR(AVAL, CNSR) ~ TRTA, cards::ADTTE) |>   ard_survival_survfit(probs = c(0.25, 0.5, 0.75)) #> {cards} data frame: 27 x 11 #>    group1 group1_level variable variable_level stat_name stat_label stat #> 1    TRTA      Placebo     prob           0.25  estimate  Survival…   70 #> 2    TRTA      Placebo     prob           0.25 conf.high  CI Upper…  177 #> 3    TRTA      Placebo     prob           0.25  conf.low  CI Lower…   35 #> 4    TRTA      Placebo     prob            0.5  estimate  Survival…   NA #> 5    TRTA      Placebo     prob            0.5 conf.high  CI Upper…   NA #> 6    TRTA      Placebo     prob            0.5  conf.low  CI Lower…   NA #> 7    TRTA      Placebo     prob           0.75  estimate  Survival…   NA #> 8    TRTA      Placebo     prob           0.75 conf.high  CI Upper…   NA #> 9    TRTA      Placebo     prob           0.75  conf.low  CI Lower…   NA #> 10   TRTA    Xanomeli…     prob           0.25  estimate  Survival…   14 #> ℹ 17 more rows #> ℹ Use `print(n = ...)` to see more rows #> ℹ 4 more variables: context, fmt_fn, warning, error  # Competing Risks Example --------------------------- set.seed(1) ADTTE_MS <- cards::ADTTE %>%   dplyr::mutate(     CNSR = dplyr::case_when(       CNSR == 0 ~ \"censor\",       runif(dplyr::n()) < 0.5 ~ \"death from cancer\",       TRUE ~ \"death other causes\"     ) %>% factor()   )  survfit(Surv(AVAL, CNSR) ~ TRTA, data = ADTTE_MS) %>%   ard_survival_survfit(times = c(60, 180)) #> Multi-state model detected. Showing probabilities into state 'death from #> cancer'. #> {cards} data frame: 18 x 11 #>    group1 group1_level variable variable_level stat_name stat_label  stat #> 1    TRTA      Placebo     time             60  estimate  Survival… 0.054 #> 2    TRTA      Placebo     time             60 conf.high  CI Upper…  0.14 #> 3    TRTA      Placebo     time             60  conf.low  CI Lower… 0.021 #> 4    TRTA      Placebo     time            180  estimate  Survival… 0.226 #> 5    TRTA      Placebo     time            180 conf.high  CI Upper… 0.361 #> 6    TRTA      Placebo     time            180  conf.low  CI Lower… 0.142 #> 7    TRTA    Xanomeli…     time             60  estimate  Survival… 0.137 #> 8    TRTA    Xanomeli…     time             60 conf.high  CI Upper… 0.311 #> 9    TRTA    Xanomeli…     time             60  conf.low  CI Lower…  0.06 #> 10   TRTA    Xanomeli…     time            180  estimate  Survival…  0.51 #> 11   TRTA    Xanomeli…     time            180 conf.high  CI Upper… 0.892 #> 12   TRTA    Xanomeli…     time            180  conf.low  CI Lower… 0.292 #> 13   TRTA    Xanomeli…     time             60  estimate  Survival… 0.162 #> 14   TRTA    Xanomeli…     time             60 conf.high  CI Upper…  0.33 #> 15   TRTA    Xanomeli…     time             60  conf.low  CI Lower…  0.08 #> 16   TRTA    Xanomeli…     time            180  estimate  Survival… 0.244 #> 17   TRTA    Xanomeli…     time            180 conf.high  CI Upper… 0.516 #> 18   TRTA    Xanomeli…     time            180  conf.low  CI Lower… 0.115 #> ℹ 4 more variables: context, fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/cardx-package.html","id":null,"dir":"Reference","previous_headings":"","what":"cardx: Extra Analysis Results Data Utilities — cardx-package","title":"cardx: Extra Analysis Results Data Utilities — cardx-package","text":"Create extra Analysis Results Data (ARD) summary objects. package supplements simple ARD functions 'cards' package, exporting functions put statistical results ARD format. objects used re-used construct summary tables, visualizations, written reports.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/cardx/main/reference/cardx-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"cardx: Extra Analysis Results Data Utilities — cardx-package","text":"Maintainer: Daniel Sjoberg danield.sjoberg@gmail.com Authors: Abinaya Yogasekaram abinaya.yogasekaram@contractors.roche.com Emily de la Rua emily.de_la_rua@contractors.roche.com contributors: F. Hoffmann-La Roche AG [copyright holder, funder]","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/construction_helpers.html","id":null,"dir":"Reference","previous_headings":"","what":"Construction Helpers — construction_helpers","title":"Construction Helpers — construction_helpers","text":"functions help construct calls various types models.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/construction_helpers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Construction Helpers — construction_helpers","text":"","code":"construct_model(x, ...)  # S3 method for data.frame construct_model(   x,   formula,   method,   method.args = list(),   package = \"base\",   env = caller_env(),   ... )  # S3 method for survey.design construct_model(   x,   formula,   method,   method.args = list(),   package = \"survey\",   env = caller_env(),   ... )  reformulate2(   termlabels,   response = NULL,   intercept = TRUE,   pattern_term = \"[ \\n\\r]\",   pattern_response = \"[ \\n\\r]\",   env = parent.frame() )  bt(x, pattern = \"[ \\n\\r]\")  bt_strip(x)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/construction_helpers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Construction Helpers — construction_helpers","text":"x construct_model.data.frame() (data.frame) data frame construct_model.survey.design() (survey.design) survey design object bt()/bt_strip() (character) character vector, typically variable names ... dots future extensions must empty. formula (formula) formula method (string) string naming function called, e.g. \"glm\". function belongs library attached, package name must specified package argument. method.args (named list) named list arguments passed fn. package (string) string package name temporarily loaded function specified method executed. env environment evaluate expr. environment applicable quosures environments. termlabels character vector giving right-hand side     model formula.  zero-length. response character string, symbol call giving left-hand     side model formula, NULL. intercept logical: formula intercept? pattern_term, pattern_response passed bt(pattern) arguments stats::reformulate(termlabels, response). pattern (string) regular expression string. regex matches, backticks added string. NULL, backticks added.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/construction_helpers.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Construction Helpers — construction_helpers","text":"depends calling function","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/construction_helpers.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Construction Helpers — construction_helpers","text":"construct_model(): Builds models form method(data = data, formula = formula, method.args!!!). package argument specified, package temporarily attached model evaluated. reformulate2(): copy reformulate() except variable names contain space wrapped backticks. bt(): Adds backticks character vector. bt_strip(): Removes backticks string begins ends backtick.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/construction_helpers.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Construction Helpers — construction_helpers","text":"","code":"construct_model(   x = mtcars,   formula = am ~ mpg + (1 | vs),   method = \"glmer\",   method.args = list(family = binomial),   package = \"lme4\" ) #> Generalized linear mixed model fit by maximum likelihood (Laplace #>   Approximation) [glmerMod] #>  Family: binomial  ( logit ) #> Formula: am ~ mpg + (1 | vs) #>    Data: structure(list(mpg = c(21, 21, 22.8, 21.4, 18.7, 18.1, 14.3,   #> 24.4, 22.8, 19.2, 17.8, 16.4, 17.3, 15.2, 10.4, 10.4, 14.7, 32.4,   #> 30.4, 33.9, 21.5, 15.5, 15.2, 13.3, 19.2, 27.3, 26, 30.4, 15.8,   #> 19.7, 15, 21.4), cyl = c(6, 6, 4, 6, 8, 6, 8, 4, 4, 6, 6, 8,   #> 8, 8, 8, 8, 8, 4, 4, 4, 4, 8, 8, 8, 8, 4, 4, 4, 8, 6, 8, 4),   #>     disp = c(160, 160, 108, 258, 360, 225, 360, 146.7, 140.8,   #>     167.6, 167.6, 275.8, 275.8, 275.8, 472, 460, 440, 78.7, 75.7,   #>     71.1, 120.1, 318, 304, 350, 400, 79, 120.3, 95.1, 351, 145,   #>     301, 121), hp = c(110, 110, 93, 110, 175, 105, 245, 62, 95,   #>     123, 123, 180, 180, 180, 205, 215, 230, 66, 52, 65, 97, 150,   #>     150, 245, 175, 66, 91, 113, 264, 175, 335, 109), drat = c(3.9,   #>     3.9, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 3.92, 3.92, 3.92,   #>     3.07, 3.07, 3.07, 2.93, 3, 3.23, 4.08, 4.93, 4.22, 3.7, 2.76,   #>     3.15, 3.73, 3.08, 4.08, 4.43, 3.77, 4.22, 3.62, 3.54, 4.11  #>     ), wt = c(2.62, 2.875, 2.32, 3.215, 3.44, 3.46, 3.57, 3.19,   #>     3.15, 3.44, 3.44, 4.07, 3.73, 3.78, 5.25, 5.424, 5.345, 2.2,   #>     1.615, 1.835, 2.465, 3.52, 3.435, 3.84, 3.845, 1.935, 2.14,   #>     1.513, 3.17, 2.77, 3.57, 2.78), qsec = c(16.46, 17.02, 18.61,   #>     19.44, 17.02, 20.22, 15.84, 20, 22.9, 18.3, 18.9, 17.4, 17.6,   #>     18, 17.98, 17.82, 17.42, 19.47, 18.52, 19.9, 20.01, 16.87,   #>     17.3, 15.41, 17.05, 18.9, 16.7, 16.9, 14.5, 15.5, 14.6, 18.6  #>     ), vs = c(0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0,   #>     0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1), am = c(1,   #>     1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1,   #>     0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1), gear = c(4, 4, 4, 3,   #>     3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 3, 3,   #>     3, 3, 4, 5, 5, 5, 5, 5, 4), carb = c(4, 4, 1, 1, 2, 1, 4,   #>     2, 2, 4, 4, 3, 3, 3, 4, 4, 4, 1, 2, 1, 1, 2, 2, 4, 2, 1,   #>     2, 2, 4, 6, 8, 2)), row.names = c(\"Mazda RX4\", \"Mazda RX4 Wag\",   #> \"Datsun 710\", \"Hornet 4 Drive\", \"Hornet Sportabout\", \"Valiant\",   #> \"Duster 360\", \"Merc 240D\", \"Merc 230\", \"Merc 280\", \"Merc 280C\",   #> \"Merc 450SE\", \"Merc 450SL\", \"Merc 450SLC\", \"Cadillac Fleetwood\",   #> \"Lincoln Continental\", \"Chrysler Imperial\", \"Fiat 128\", \"Honda Civic\",   #> \"Toyota Corolla\", \"Toyota Corona\", \"Dodge Challenger\", \"AMC Javelin\",   #> \"Camaro Z28\", \"Pontiac Firebird\", \"Fiat X1-9\", \"Porsche 914-2\",   #> \"Lotus Europa\", \"Ford Pantera L\", \"Ferrari Dino\", \"Maserati Bora\",   #> \"Volvo 142E\"), class = \"data.frame\") #>      AIC      BIC   logLik deviance df.resid  #>  35.2503  39.6475 -14.6251  29.2503       29  #> Random effects: #>  Groups Name        Std.Dev. #>  vs     (Intercept) 0.7896   #> Number of obs: 32, groups:  vs, 2 #> Fixed Effects: #> (Intercept)          mpg   #>     -8.7018       0.4085    construct_model(   x = mtcars |> dplyr::rename(`M P G` = mpg),   formula = reformulate2(c(\"M P G\", \"cyl\"), response = \"hp\"),   method = \"lm\" ) |>   ard_regression() |>   dplyr::filter(stat_name %in% c(\"term\", \"estimate\", \"p.value\")) #> {cards} data frame: 6 x 7 #>   variable variable_level   context stat_name stat_label    stat #> 1    M P G             NA regressi…      term       term `M P G` #> 2    M P G             NA regressi…  estimate  Coeffici…  -2.775 #> 3    M P G             NA regressi…   p.value    p-value   0.213 #> 4      cyl             NA regressi…      term       term     cyl #> 5      cyl             NA regressi…  estimate  Coeffici…  23.979 #> 6      cyl             NA regressi…   p.value    p-value   0.003 #> ℹ 1 more variable: fmt_fn"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-extract_wald_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract data from wald.test object — .extract_wald_results","title":"Extract data from wald.test object — .extract_wald_results","text":"Extract data wald.test object","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-extract_wald_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract data from wald.test object — .extract_wald_results","text":"","code":".extract_wald_results(wald_test)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-extract_wald_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract data from wald.test object — .extract_wald_results","text":"wald_test (data.frame) wald test object object aod::wald.test()","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-extract_wald_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract data from wald.test object — .extract_wald_results","text":"data frame containing wald test results.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_cohens_d_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert Cohen's D Test to ARD — .format_cohens_d_results","title":"Convert Cohen's D Test to ARD — .format_cohens_d_results","text":"Convert Cohen's D Test ARD","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_cohens_d_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert Cohen's D Test to ARD — .format_cohens_d_results","text":"","code":".format_cohens_d_results(by, variable, lst_tidy, paired, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_cohens_d_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert Cohen's D Test to ARD — .format_cohens_d_results","text":"(string) column name variable (string) variable column name lst_tidy (named list) list tidied results constructed eval_capture_conditions(), e.g. eval_capture_conditions(t.test(mtcars$mpg ~ mtcars$) |> broom::tidy()). paired TRUE, values x y considered paired. produces effect size equivalent one-sample effect size x - y. See also repeated_measures_d() options. ... passed cohens_d(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_cohens_d_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert Cohen's D Test to ARD — .format_cohens_d_results","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_cohens_d_results.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert Cohen's D Test to ARD — .format_cohens_d_results","text":"","code":"cardx:::.format_cohens_d_results(   by = \"ARM\",   variable = \"AGE\",   paired = FALSE,   lst_tidy =     cards::eval_capture_conditions(       effectsize::hedges_g(data[[variable]] ~ data[[by]], paired = FALSE) |>         parameters::standardize_names(style = \"broom\")     ) ) #> {cards} data frame: 8 x 9 #>   group1 variable   stat_name stat_label      stat     error #> 1    ARM      AGE    estimate  Effect S…           could no… #> 2    ARM      AGE  conf.level  CI Confi…           could no… #> 3    ARM      AGE    conf.low  CI Lower…           could no… #> 4    ARM      AGE   conf.high  CI Upper…           could no… #> 5    ARM      AGE          mu    H0 Mean         0 could no… #> 6    ARM      AGE      paired  Paired t…     FALSE could no… #> 7    ARM      AGE   pooled_sd  Pooled S…      TRUE could no… #> 8    ARM      AGE alternative  Alternat… two.sided could no… #> ℹ 3 more variables: context, fmt_fn, warning"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_hedges_g_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert Hedge's G Test to ARD — .format_hedges_g_results","title":"Convert Hedge's G Test to ARD — .format_hedges_g_results","text":"Convert Hedge's G Test ARD","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_hedges_g_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert Hedge's G Test to ARD — .format_hedges_g_results","text":"","code":".format_hedges_g_results(by, variable, lst_tidy, paired, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_hedges_g_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert Hedge's G Test to ARD — .format_hedges_g_results","text":"(string) column name variable (string) variable column name lst_tidy (named list) list tidied results constructed eval_capture_conditions(), e.g. eval_capture_conditions(t.test(mtcars$mpg ~ mtcars$) |> broom::tidy()). paired TRUE, values x y considered paired. produces effect size equivalent one-sample effect size x - y. See also repeated_measures_d() options. ... passed hedges_g(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_hedges_g_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert Hedge's G Test to ARD — .format_hedges_g_results","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_hedges_g_results.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert Hedge's G Test to ARD — .format_hedges_g_results","text":"","code":"cardx:::.format_hedges_g_results(   by = \"ARM\",   variable = \"AGE\",   paired = FALSE,   lst_tidy =     cards::eval_capture_conditions(       effectsize::hedges_g(data[[variable]] ~ data[[by]], paired = FALSE) |>         parameters::standardize_names(style = \"broom\")     ) ) #> {cards} data frame: 8 x 9 #>   group1 variable   stat_name stat_label      stat     error #> 1    ARM      AGE    estimate  Effect S…           could no… #> 2    ARM      AGE  conf.level  CI Confi…           could no… #> 3    ARM      AGE    conf.low  CI Lower…           could no… #> 4    ARM      AGE   conf.high  CI Upper…           could no… #> 5    ARM      AGE          mu    H0 Mean         0 could no… #> 6    ARM      AGE      paired  Paired t…     FALSE could no… #> 7    ARM      AGE   pooled_sd  Pooled S…      TRUE could no… #> 8    ARM      AGE alternative  Alternat… two.sided could no… #> ℹ 3 more variables: context, fmt_fn, warning"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_mcnemartest_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert McNemar's test to ARD — .format_mcnemartest_results","title":"Convert McNemar's test to ARD — .format_mcnemartest_results","text":"Convert McNemar's test ARD","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_mcnemartest_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert McNemar's test to ARD — .format_mcnemartest_results","text":"","code":".format_mcnemartest_results(by, variable, lst_tidy, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_mcnemartest_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert McNemar's test to ARD — .format_mcnemartest_results","text":"(string) column name variable (string) variable column name lst_tidy (named list) list tidied results constructed eval_capture_conditions(), e.g. eval_capture_conditions(t.test(mtcars$mpg ~ mtcars$) |> broom::tidy()). ... passed stats::mcnemar.test(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_mcnemartest_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert McNemar's test to ARD — .format_mcnemartest_results","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_mcnemartest_results.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert McNemar's test to ARD — .format_mcnemartest_results","text":"","code":"cardx:::.format_mcnemartest_results(   by = \"ARM\",   variable = \"AGE\",   lst_tidy =     cards::eval_capture_conditions(       stats::mcnemar.test(cards::ADSL[[\"SEX\"]], cards::ADSL[[\"EFFFL\"]]) |>         broom::tidy()     ) ) #> {cards} data frame: 5 x 9 #>   group1 variable   context stat_name stat_label      stat #> 1    ARM      AGE stats_mc… statistic  X-square…    111.91 #> 2    ARM      AGE stats_mc…   p.value    p-value         0 #> 3    ARM      AGE stats_mc… parameter  Degrees …         1 #> 4    ARM      AGE stats_mc…    method     method McNemar'… #> 5    ARM      AGE stats_mc…   correct    correct      TRUE #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_moodtest_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert mood test results to ARD — .format_moodtest_results","title":"Convert mood test results to ARD — .format_moodtest_results","text":"Convert mood test results ARD","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_moodtest_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert mood test results to ARD — .format_moodtest_results","text":"","code":".format_moodtest_results(by, variable, lst_tidy, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_moodtest_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert mood test results to ARD — .format_moodtest_results","text":"(string) column name variable (string) variable column name lst_tidy (named list) list tidied results constructed eval_capture_conditions(), e.g. eval_capture_conditions(t.test(mtcars$mpg ~ mtcars$) |> broom::tidy()). ... passed mood.test(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_moodtest_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert mood test results to ARD — .format_moodtest_results","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_moodtest_results.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert mood test results to ARD — .format_moodtest_results","text":"","code":"cardx:::.format_moodtest_results(   by = \"SEX\",   variable = \"AGE\",   lst_tidy =     cards::eval_capture_conditions(       stats::mood.test(ADSL[[\"AGE\"]] ~ ADSL[[\"SEX\"]]) |>         broom::tidy()     ) ) #> {cards} data frame: 4 x 9 #>   group1 variable   stat_name stat_label stat     error #> 1    SEX      AGE   statistic  Z-Statis…      object '… #> 2    SEX      AGE     p.value    p-value      object '… #> 3    SEX      AGE      method     method      object '… #> 4    SEX      AGE alternative  Alternat…      object '… #> ℹ 3 more variables: context, fmt_fn, warning"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_proptest_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert prop.test to ARD — .format_proptest_results","title":"Convert prop.test to ARD — .format_proptest_results","text":"Convert prop.test ARD","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_proptest_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert prop.test to ARD — .format_proptest_results","text":"","code":".format_proptest_results(by, variable, lst_tidy, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_proptest_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert prop.test to ARD — .format_proptest_results","text":"(string) column name variable (string) variable column name lst_tidy (named list) list tidied results constructed eval_capture_conditions(), e.g. eval_capture_conditions(t.test(mtcars$mpg ~ mtcars$) |> broom::tidy()). ... passed prop.test(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_proptest_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert prop.test to ARD — .format_proptest_results","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_survfit_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert Tidied Survival Fit to ARD — .format_survfit_results","title":"Convert Tidied Survival Fit to ARD — .format_survfit_results","text":"Convert Tidied Survival Fit ARD","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_survfit_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert Tidied Survival Fit to ARD — .format_survfit_results","text":"","code":".format_survfit_results(tidy_survfit)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_survfit_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert Tidied Survival Fit to ARD — .format_survfit_results","text":"ARD data frame class 'card'","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_survfit_results.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert Tidied Survival Fit to ARD — .format_survfit_results","text":"","code":"cardx:::.format_survfit_results(   broom::tidy(survival::survfit(survival::Surv(AVAL, CNSR) ~ TRTA, cards::ADTTE)) ) #> {cards} data frame: 483 x 14 #>    group1 group1_level variable variable_level stat_name stat_label stat n.risk #> 1    TRTA      Placebo     time              1  estimate  Survival…    1     86 #> 2    TRTA      Placebo     time              1 conf.high  CI Upper…    1     86 #> 3    TRTA      Placebo     time              1  conf.low  CI Lower…    1     86 #> 4    TRTA      Placebo     time              2  estimate  Survival…    1     85 #> 5    TRTA      Placebo     time              2 conf.high  CI Upper…    1     85 #> 6    TRTA      Placebo     time              2  conf.low  CI Lower…    1     85 #> 7    TRTA      Placebo     time              3  estimate  Survival…    1     84 #> 8    TRTA      Placebo     time              3 conf.high  CI Upper…    1     84 #> 9    TRTA      Placebo     time              3  conf.low  CI Lower…    1     84 #> 10   TRTA      Placebo     time              7  estimate  Survival…    1     82 #>    n.event n.censor std.error #> 1        0        1         0 #> 2        0        1         0 #> 3        0        1         0 #> 4        0        1         0 #> 5        0        1         0 #> 6        0        1         0 #> 7        0        2         0 #> 8        0        2         0 #> 9        0        2         0 #> 10       0        1         0 #> ℹ 473 more rows #> ℹ Use `print(n = ...)` to see more rows #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_ttest_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert t-test to ARD — .format_ttest_results","title":"Convert t-test to ARD — .format_ttest_results","text":"Convert t-test ARD","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_ttest_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert t-test to ARD — .format_ttest_results","text":"","code":".format_ttest_results(by = NULL, variable, lst_tidy, paired, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_ttest_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert t-test to ARD — .format_ttest_results","text":"(string) column name variable (string) variable column name lst_tidy (named list) list tidied results constructed eval_capture_conditions(), e.g. eval_capture_conditions(t.test(mtcars$mpg ~ mtcars$) |> broom::tidy()). paired logical indicating whether want paired     t-test. ... passed t.test(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_ttest_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert t-test to ARD — .format_ttest_results","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_ttest_results.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert t-test to ARD — .format_ttest_results","text":"","code":"cardx:::.format_ttest_results(   by = \"ARM\",   variable = \"AGE\",   paired = FALSE,   lst_tidy =     cards::eval_capture_conditions(       stats::t.test(ADSL[[\"AGE\"]] ~ ADSL[[\"ARM\"]], paired = FALSE) |>         broom::tidy()     ) ) #> {cards} data frame: 14 x 9 #>    group1 variable   stat_name stat_label  stat     error #> 1     ARM      AGE    estimate  Mean Dif…       object '… #> 2     ARM      AGE   estimate1  Group 1 …       object '… #> 3     ARM      AGE   estimate2  Group 2 …       object '… #> 4     ARM      AGE   statistic  t Statis…       object '… #> 5     ARM      AGE     p.value    p-value       object '… #> 6     ARM      AGE   parameter  Degrees …       object '… #> 7     ARM      AGE    conf.low  CI Lower…       object '… #> 8     ARM      AGE   conf.high  CI Upper…       object '… #> 9     ARM      AGE      method     method       object '… #> 10    ARM      AGE alternative  alternat…       object '… #> 11    ARM      AGE          mu    H0 Mean     0 object '… #> 12    ARM      AGE      paired  Paired t… FALSE object '… #> 13    ARM      AGE   var.equal  Equal Va… FALSE object '… #> 14    ARM      AGE  conf.level  CI Confi…  0.95 object '… #> ℹ 3 more variables: context, fmt_fn, warning"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_wilcoxtest_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert Wilcoxon test to ARD — .format_wilcoxtest_results","title":"Convert Wilcoxon test to ARD — .format_wilcoxtest_results","text":"Convert Wilcoxon test ARD","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_wilcoxtest_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert Wilcoxon test to ARD — .format_wilcoxtest_results","text":"","code":".format_wilcoxtest_results(by = NULL, variable, lst_tidy, paired, ...)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_wilcoxtest_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert Wilcoxon test to ARD — .format_wilcoxtest_results","text":"(string) column name variable (string) variable column name lst_tidy (named list) list tidied results constructed eval_capture_conditions(), e.g. eval_capture_conditions(t.test(mtcars$mpg ~ mtcars$) |> broom::tidy()). paired logical indicating whether want paired test. ... passed stats::wilcox.test(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_wilcoxtest_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert Wilcoxon test to ARD — .format_wilcoxtest_results","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-format_wilcoxtest_results.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert Wilcoxon test to ARD — .format_wilcoxtest_results","text":"","code":"# Pre-processing ADSL to have grouping factor (ARM here) with 2 levels ADSL <- cards::ADSL |>   dplyr::filter(ARM %in% c(\"Placebo\", \"Xanomeline High Dose\")) |>   ard_stats_wilcox_test(by = \"ARM\", variables = \"AGE\")  cardx:::.format_wilcoxtest_results(   by = \"ARM\",   variable = \"AGE\",   paired = FALSE,   lst_tidy =     cards::eval_capture_conditions(       stats::wilcox.test(ADSL[[\"AGE\"]] ~ ADSL[[\"ARM\"]], paired = FALSE) |>         broom::tidy()     ) ) #> {cards} data frame: 12 x 9 #>    group1 variable   stat_name stat_label  stat     error #> 1     ARM      AGE   statistic  X-square…       invalid … #> 2     ARM      AGE     p.value    p-value       invalid … #> 3     ARM      AGE      method     method       invalid … #> 4     ARM      AGE alternative  alternat…       invalid … #> 5     ARM      AGE          mu         mu     0 invalid … #> 6     ARM      AGE      paired  Paired t… FALSE invalid … #> 7     ARM      AGE       exact      exact       invalid … #> 8     ARM      AGE     correct    correct  TRUE invalid … #> 9     ARM      AGE    conf.int   conf.int FALSE invalid … #> 10    ARM      AGE  conf.level  CI Confi…  0.95 invalid … #> 11    ARM      AGE    tol.root   tol.root     0 invalid … #> 12    ARM      AGE digits.rank  digits.r…   Inf invalid … #> ℹ 3 more variables: context, fmt_fn, warning"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-paired_data_pivot_wider.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert long paired data to wide — .paired_data_pivot_wider","title":"Convert long paired data to wide — .paired_data_pivot_wider","text":"Convert long paired data wide","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-paired_data_pivot_wider.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert long paired data to wide — .paired_data_pivot_wider","text":"","code":".paired_data_pivot_wider(data, by, variable, id)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-paired_data_pivot_wider.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert long paired data to wide — .paired_data_pivot_wider","text":"data (data.frame) data frame one line per subject per group (string) column name variable (string) variable column name id (string) subject id column name","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-paired_data_pivot_wider.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert long paired data to wide — .paired_data_pivot_wider","text":"wide data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-paired_data_pivot_wider.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert long paired data to wide — .paired_data_pivot_wider","text":"","code":"cards::ADSL[c(\"ARM\", \"AGE\")] |>   dplyr::filter(ARM %in% c(\"Placebo\", \"Xanomeline High Dose\")) |>   dplyr::mutate(.by = ARM, USUBJID = dplyr::row_number()) |>   dplyr::arrange(USUBJID, ARM) |>   cardx:::.paired_data_pivot_wider(by = \"ARM\", variable = \"AGE\", id = \"USUBJID\") #> # A tibble: 86 × 3 #>    USUBJID   by1   by2 #>      <int> <dbl> <dbl> #>  1       1    63    71 #>  2       2    64    77 #>  3       3    85    81 #>  4       4    52    75 #>  5       5    84    57 #>  6       6    79    56 #>  7       7    81    79 #>  8       8    69    56 #>  9       9    63    61 #> 10      10    81    56 #> # ℹ 76 more rows"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-process_survfit_probs.html","id":null,"dir":"Reference","previous_headings":"","what":"Process Survival Fit For Quantile Estimates — .process_survfit_probs","title":"Process Survival Fit For Quantile Estimates — .process_survfit_probs","text":"Process Survival Fit Quantile Estimates","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-process_survfit_probs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Process Survival Fit For Quantile Estimates — .process_survfit_probs","text":"","code":".process_survfit_probs(x, probs)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-process_survfit_probs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Process Survival Fit For Quantile Estimates — .process_survfit_probs","text":"x (survival::survfit()) survival::survfit() object. See details. probs (numeric) vector probabilities values (0,1) specifying survival quantiles return.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-process_survfit_probs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Process Survival Fit For Quantile Estimates — .process_survfit_probs","text":"tibble","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-process_survfit_probs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Process Survival Fit For Quantile Estimates — .process_survfit_probs","text":"","code":"survival::survfit(survival::Surv(AVAL, CNSR) ~ TRTA, cards::ADTTE) |>   cardx:::.process_survfit_probs(probs = c(0.25, 0.75)) #> # A tibble: 6 × 6 #>   strata                    estimate conf.low conf.high  prob context          #>   <chr>                        <dbl>    <dbl>     <dbl> <dbl> <chr>            #> 1 TRTA=Placebo                   142       70       181  0.25 survival_survfit #> 2 TRTA=Xanomeline High Dose       44       22       180  0.25 survival_survfit #> 3 TRTA=Xanomeline Low Dose        49       37       180  0.25 survival_survfit #> 4 TRTA=Placebo                   184      183       191  0.75 survival_survfit #> 5 TRTA=Xanomeline High Dose      188      167        NA  0.75 survival_survfit #> 6 TRTA=Xanomeline Low Dose       184      180        NA  0.75 survival_survfit"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-process_survfit_time.html","id":null,"dir":"Reference","previous_headings":"","what":"Process Survival Fit For Time Estimates — .process_survfit_time","title":"Process Survival Fit For Time Estimates — .process_survfit_time","text":"Process Survival Fit Time Estimates","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-process_survfit_time.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Process Survival Fit For Time Estimates — .process_survfit_time","text":"","code":".process_survfit_time(x, times, type)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-process_survfit_time.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Process Survival Fit For Time Estimates — .process_survfit_time","text":"x (survival::survfit()) survival::survfit() object. See details. times (numeric) vector times return survival probabilities. type (string NULL) type statistic report. Available Kaplan-Meier time estimates , otherwise type ignored. Default NULL. Must one following:","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-process_survfit_time.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Process Survival Fit For Time Estimates — .process_survfit_time","text":"tibble","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-process_survfit_time.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Process Survival Fit For Time Estimates — .process_survfit_time","text":"","code":"survival::survfit(survival::Surv(AVAL, CNSR) ~ TRTA, cards::ADTTE) |>   cardx:::.process_survfit_time(times = c(60, 180), type = \"risk\") #> # A tibble: 6 × 6 #>    time estimate conf.low conf.high strata                    context #>   <dbl>    <dbl>    <dbl>     <dbl> <fct>                     <chr>   #> 1    60    0.107   0.0338     0.175 TRTA=Placebo              risk    #> 2    60    0.306   0.151      0.432 TRTA=Xanomeline High Dose risk    #> 3    60    0.268   0.122      0.390 TRTA=Xanomeline Low Dose  risk    #> 4   180    0.349   0.217      0.459 TRTA=Placebo              risk    #> 5   180    0.738   0.251      0.908 TRTA=Xanomeline High Dose risk    #> 6   180    0.619   0.257      0.805 TRTA=Xanomeline Low Dose  risk"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-strata_normal_quantile.html","id":null,"dir":"Reference","previous_headings":"","what":"Helper Function for the Estimation of Stratified Quantiles — .strata_normal_quantile","title":"Helper Function for the Estimation of Stratified Quantiles — .strata_normal_quantile","text":"function wraps estimation stratified percentiles assume approximation large numbers. necessary case proportions strata unequal.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-strata_normal_quantile.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Helper Function for the Estimation of Stratified Quantiles — .strata_normal_quantile","text":"","code":".strata_normal_quantile(vars, weights, conf.level)"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-strata_normal_quantile.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Helper Function for the Estimation of Stratified Quantiles — .strata_normal_quantile","text":"weights (numeric NULL) weights level strata. NULL, estimated using iterative algorithm minimizes weighted squared length confidence interval. conf.level (numeric) scalar (0, 1) indicating confidence level. Default 0.95","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-strata_normal_quantile.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Helper Function for the Estimation of Stratified Quantiles — .strata_normal_quantile","text":"Stratified quantile.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-strata_normal_quantile.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Helper Function for the Estimation of Stratified Quantiles — .strata_normal_quantile","text":"","code":"strata_data <- table(data.frame(   \"f1\" = sample(c(TRUE, FALSE), 100, TRUE),   \"f2\" = sample(c(\"x\", \"y\", \"z\"), 100, TRUE),   stringsAsFactors = TRUE )) ns <- colSums(strata_data) ests <- strata_data[\"TRUE\", ] / ns vars <- ests * (1 - ests) / ns weights <- rep(1 / length(ns), length(ns))  cardx:::.strata_normal_quantile(vars, weights, 0.95) #> [1] 1.134584"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-update_weights_strat_wilson.html","id":null,"dir":"Reference","previous_headings":"","what":"Helper Function for the Estimation of Weights for proportion_ci_strat_wilson() — .update_weights_strat_wilson","title":"Helper Function for the Estimation of Weights for proportion_ci_strat_wilson() — .update_weights_strat_wilson","text":"function wraps iteration procedure allows estimate weights proportional strata. assumes minimize weighted squared length confidence interval.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-update_weights_strat_wilson.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Helper Function for the Estimation of Weights for proportion_ci_strat_wilson() — .update_weights_strat_wilson","text":"","code":".update_weights_strat_wilson(   vars,   strata_qnorm,   initial_weights,   n_per_strata,   max.iterations = 50,   conf.level = 0.95,   tol = 0.001 )"},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-update_weights_strat_wilson.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Helper Function for the Estimation of Weights for proportion_ci_strat_wilson() — .update_weights_strat_wilson","text":"vars (numeric) normalized proportions strata. strata_qnorm (numeric) initial estimation identical weights quantiles. initial_weights (numeric) initial weights used calculate strata_qnorm. can optimized future need estimate better initial weights. n_per_strata (numeric) number elements strata. max.iterations (count) maximum number iterations tried. Convergence always checked. conf.level (numeric) scalar (0, 1) indicating confidence level. Default 0.95 tol (number) tolerance threshold convergence.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-update_weights_strat_wilson.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Helper Function for the Estimation of Weights for proportion_ci_strat_wilson() — .update_weights_strat_wilson","text":"list 3 elements: n_it, weights, diff_v.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/cardx/main/reference/dot-update_weights_strat_wilson.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Helper Function for the Estimation of Weights for proportion_ci_strat_wilson() — .update_weights_strat_wilson","text":"","code":"vs <- c(0.011, 0.013, 0.012, 0.014, 0.017, 0.018) sq <- 0.674 ws <- rep(1 / length(vs), length(vs)) ns <- c(22, 18, 17, 17, 14, 12)  cardx:::.update_weights_strat_wilson(vs, sq, ws, ns, 100, 0.95, 0.001) #> $n_it #> [1] 3 #>  #> $weights #> [1] 0.2067191 0.1757727 0.1896962 0.1636346 0.1357615 0.1284160 #>  #> $diff_v #> [1] 1.458717e-01 1.497223e-03 1.442189e-06 #>"},{"path":"https://insightsengineering.github.io/cardx/main/reference/proportion_ci.html","id":null,"dir":"Reference","previous_headings":"","what":"Functions for Calculating Proportion Confidence Intervals — proportion_ci","title":"Functions for Calculating Proportion Confidence Intervals — proportion_ci","text":"Functions calculate different proportion confidence intervals use ard_proportion().","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/proportion_ci.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Functions for Calculating Proportion Confidence Intervals — proportion_ci","text":"","code":"proportion_ci_wald(x, conf.level = 0.95, correct = FALSE)  proportion_ci_wilson(x, conf.level = 0.95, correct = FALSE)  proportion_ci_clopper_pearson(x, conf.level = 0.95)  proportion_ci_agresti_coull(x, conf.level = 0.95)  proportion_ci_jeffreys(x, conf.level = 0.95)  proportion_ci_strat_wilson(   x,   strata,   weights = NULL,   conf.level = 0.95,   max.iterations = 10L,   correct = FALSE )"},{"path":"https://insightsengineering.github.io/cardx/main/reference/proportion_ci.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Functions for Calculating Proportion Confidence Intervals — proportion_ci","text":"x vector binary values, .e. logical vector, numeric values c(0, 1) conf.level (numeric) scalar (0, 1) indicating confidence level. Default 0.95 correct (flag) include continuity correction. information, see example stats::prop.test(). strata (factor) variable one level per stratum length x. weights (numeric NULL) weights level strata. NULL, estimated using iterative algorithm minimizes weighted squared length confidence interval. max.iterations (count) maximum number iterations iterative procedure used find estimates optimal weights.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/proportion_ci.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Functions for Calculating Proportion Confidence Intervals — proportion_ci","text":"Confidence interval proportion.","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/proportion_ci.html","id":"functions","dir":"Reference","previous_headings":"","what":"Functions","title":"Functions for Calculating Proportion Confidence Intervals — proportion_ci","text":"proportion_ci_wald(): Calculates Wald interval following usual textbook definition single proportion confidence interval using normal approximation. $$\\hat{p} \\pm z_{\\alpha/2} \\sqrt{\\frac{\\hat{p}(1 - \\hat{p})}{n}}$$ proportion_ci_wilson(): Calculates Wilson interval calling stats::prop.test(). Also referred Wilson score interval. $$\\frac{\\hat{p} + \\frac{z^2_{\\alpha/2}}{2n} \\pm z_{\\alpha/2} \\sqrt{\\frac{\\hat{p}(1 - \\hat{p})}{n} + \\frac{z^2_{\\alpha/2}}{4n^2}}}{1 + \\frac{z^2_{\\alpha/2}}{n}}$$ proportion_ci_clopper_pearson(): Calculates Clopper-Pearson interval calling stats::binom.test(). Also referred exact method. $$ \\left( \\frac{k}{n} \\pm z_{\\alpha/2} \\sqrt{\\frac{\\frac{k}{n}(1-\\frac{k}{n})}{n} + \\frac{z^2_{\\alpha/2}}{4n^2}} \\right) / \\left( 1 + \\frac{z^2_{\\alpha/2}}{n} \\right)$$ proportion_ci_agresti_coull(): Calculates Agresti-Coull interval (created Alan Agresti Brent Coull) (95% CI) adding two successes two failures data using Wald formula construct CI. $$ \\left( \\frac{\\tilde{p} + z^2_{\\alpha/2}/2}{n + z^2_{\\alpha/2}} \\pm z_{\\alpha/2} \\sqrt{\\frac{\\tilde{p}(1 - \\tilde{p})}{n} + \\frac{z^2_{\\alpha/2}}{4n^2}} \\right)$$ proportion_ci_jeffreys(): Calculates Jeffreys interval, equal-tailed interval based non-informative Jeffreys prior binomial proportion. $$\\left( \\text{Beta}\\left(\\frac{k}{2} + \\frac{1}{2}, \\frac{n - k}{2} + \\frac{1}{2}\\right)_\\alpha, \\text{Beta}\\left(\\frac{k}{2} + \\frac{1}{2}, \\frac{n - k}{2} + \\frac{1}{2}\\right)_{1-\\alpha} \\right)$$ proportion_ci_strat_wilson(): Calculates stratified Wilson confidence interval unequal proportions described Xin YA, Su XG. Stratified Wilson Newcombe confidence intervals multiple binomial proportions. Statistics Biopharmaceutical Research. 2010;2(3). $$\\frac{\\hat{p}_j + \\frac{z^2_{\\alpha/2}}{2n_j} \\pm z_{\\alpha/2} \\sqrt{\\frac{\\hat{p}_j(1 - \\hat{p}_j)}{n_j} + \\frac{z^2_{\\alpha/2}}{4n_j^2}}}{1 + \\frac{z^2_{\\alpha/2}}{n_j}}$$","code":""},{"path":"https://insightsengineering.github.io/cardx/main/reference/proportion_ci.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Functions for Calculating Proportion Confidence Intervals — proportion_ci","text":"","code":"x <- c(   TRUE, TRUE, TRUE, TRUE, TRUE,   FALSE, FALSE, FALSE, FALSE, FALSE )  proportion_ci_wald(x, conf.level = 0.9) #> $N #> [1] 10 #>  #> $estimate #> [1] 0.5 #>  #> $conf.low #> [1] 0.2399258 #>  #> $conf.high #> [1] 0.7600742 #>  #> $conf.level #> [1] 0.9 #>  #> $method #> Wald Confidence Interval without continuity correction #>  proportion_ci_wilson(x, correct = TRUE) #> $N #> [1] 10 #>  #> $conf.level #> [1] 0.95 #>  #> $estimate #>   p  #> 0.5  #>  #> $statistic #> X-squared  #>         0  #>  #> $p.value #> [1] 1 #>  #> $parameter #> df  #>  1  #>  #> $conf.low #> [1] 0.2365931 #>  #> $conf.high #> [1] 0.7634069 #>  #> $method #> Wilson Confidence Interval with continuity correction #>  #> $alternative #> [1] \"two.sided\" #>  proportion_ci_clopper_pearson(x) #> $N #> [1] 10 #>  #> $conf.level #> [1] 0.95 #>  #> $estimate #> probability of success  #>                    0.5  #>  #> $statistic #> number of successes  #>                   5  #>  #> $p.value #> [1] 1 #>  #> $parameter #> number of trials  #>               10  #>  #> $conf.low #> [1] 0.187086 #>  #> $conf.high #> [1] 0.812914 #>  #> $method #> [1] \"Clopper-Pearson Confidence Interval\" #>  #> $alternative #> [1] \"two.sided\" #>  proportion_ci_agresti_coull(x) #> $N #> [1] 10 #>  #> $estimate #> [1] 0.5 #>  #> $conf.low #> [1] 0.2365931 #>  #> $conf.high #> [1] 0.7634069 #>  #> $conf.level #> [1] 0.95 #>  #> $method #> [1] \"Agresti-Coull Confidence Interval\" #>  proportion_ci_jeffreys(x) #> $N #> [1] 10 #>  #> $estimate #> [1] 0.5 #>  #> $conf.low #> [1] 0.2235287 #>  #> $conf.high #> [1] 0.7764713 #>  #> $conf.level #> [1] 0.95 #>  #> $method #> Jeffreys Interval #>  # Stratified Wilson confidence interval with unequal probabilities  set.seed(1) rsp <- sample(c(TRUE, FALSE), 100, TRUE) strata_data <- data.frame(   \"f1\" = sample(c(\"a\", \"b\"), 100, TRUE),   \"f2\" = sample(c(\"x\", \"y\", \"z\"), 100, TRUE),   stringsAsFactors = TRUE ) strata <- interaction(strata_data) n_strata <- ncol(table(rsp, strata)) # Number of strata  proportion_ci_strat_wilson(   x = rsp, strata = strata,   conf.level = 0.90 ) #> $N #> [1] 100 #>  #> $estimate #> [1] 0.49 #>  #> $conf.low #> [1] 0.4072891 #>  #> $conf.high #> [1] 0.5647887 #>  #> $conf.level #> [1] 0.9 #>  #> $weights #>       a.x       b.x       a.y       b.y       a.z       b.z  #> 0.2074199 0.1776464 0.1915610 0.1604678 0.1351096 0.1277952  #>  #> $method #> Stratified Wilson Confidence Interval without continuity correction #>   # Not automatic setting of weights proportion_ci_strat_wilson(   x = rsp, strata = strata,   weights = rep(1 / n_strata, n_strata),   conf.level = 0.90 ) #> $N #> [1] 100 #>  #> $estimate #> [1] 0.49 #>  #> $conf.low #> [1] 0.4190436 #>  #> $conf.high #> [1] 0.5789733 #>  #> $conf.level #> [1] 0.9 #>  #> $method #> Stratified Wilson Confidence Interval without continuity correction #>"},{"path":"https://insightsengineering.github.io/cardx/main/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. dplyr %>%, all_of, any_of, contains, ends_with, everything, last_col, matches, num_range, one_of, starts_with, ","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/cardx/main/news/index.html","id":"breaking-changes-0-1-0-9025","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"cardx 0.1.0.9025","text":"Updated function names follow pattern ard_<pkgname>_<fnname>(). Former functions names deprecated. (#106)","code":"ard_ttest()             -> ard_stats_t_test() ard_paired_ttest()      -> ard_stats_paired_t_test() ard_wilcoxtest()        -> ard_stats_wilcox_test() ard_paired_wilcoxtest() -> ard_stats_paired_wilcox_test() ard_chisqtest()         -> ard_stats_chisq_test() ard_fishertest()        -> ard_stats_fisher_test() ard_kruskaltest()       -> ard_stats_kruskal_test() ard_mcnemartest()       -> ard_stats_mcnemar_test() ard_moodtest()          -> ard_stats_mood_test()"},{"path":"https://insightsengineering.github.io/cardx/main/news/index.html","id":"new-features-0-1-0-9025","dir":"Changelog","previous_headings":"","what":"New Features","title":"cardx 0.1.0.9025","text":"Added following functions calculating Analysis Results Data (ARD). ard_stats_aov() calculating ANOVA results using stats::aov(). (#3) ard_stats_anova() calculating ANOVA results using stats::anova(). (#12) ard_stats_mcnemar_test_long() McNemar’s test long data using stats::mcnemar.test(). ard_aod_wald_test() calculating Wald Tests regression models using aod::wald.test(). (#84) ard_car_anova() calculating ANOVA results using car::Anova(). (#3) ard_stats_oneway_test() calculating ANOVA results using stats::oneway.test(). (#3) ard_effectsize_cohens_d(), ard_effectsize_paired_cohens_d(), ard_effectsize_hedges_g(), ard_effectsize_paired_hedges_g() standardized differences using effectsize::cohens_d() effectsize::hedges_g(). (#50) ard_stats_prop_test() tests proportions using stats::prop.test(). (#64) ard_regression_basic() basic regression models. function focuses matching terms underlying variables names. (#46) ard_smd_smd() calculating standardized mean differences using smd::smd(). (#4) ard_survival_survfit() survival analyses using survival::survfit(). (#43) ard_survey_svycontinuous() calculating univariate summary statistics weighted/survey data using many functions {survey} package. (#68) ard_survey_svychisq() weighted/survey chi-squared test using survey::svychisq(). (#72) ard_survey_svyttest() weighted/survey t-tests using survey::svyttest(). (#70) ard_survey_svyranktest() weighted/survey rank tests using survey::svyranktest(). (#71) ard_car_vif() calculating variance inflation factor using car::vif(). (#10) ard_emmeans_mean_difference() calculating least-squares mean differences using {emmeans} package. (#34) Updated functions ard_stats_t_test(), ard_stats_paired_t_test(), ard_stats_wilcox_test(), ard_stats_paired_wilcox_test(), ard_stats_chisq_test(), ard_stats_fisher_test(), ard_stats_kruskal_test(), ard_stats_mcnemar_test(), ard_stats_mood_test() accept multiple variables . Independent tests calculated variable. variable argument renamed variables. (#77) Updated ard_stats_t_test() ard_stats_wilcox_test() longer require argument, yields central estimates confidence intervals. (#82) Imported cli call environment functions https://github.com/ddsjoberg/standalone/blob/main/R/standalone-cli_call_env.R implemented set_cli_abort_call user-facing functions. (#111) Added ard_survival_survdiff() creating results survival::survdiff(). (#113)","code":""},{"path":"https://insightsengineering.github.io/cardx/main/news/index.html","id":"cardx-010","dir":"Changelog","previous_headings":"","what":"cardx 0.1.0","title":"cardx 0.1.0","text":"CRAN release: 2024-03-18 Initial release.","code":""}]
+[{"path":[]},{"path":"https://insightsengineering.github.io/cardx/CODE_OF_CONDUCT.html","id":"our-pledge","dir":"","previous_headings":"","what":"Our Pledge","title":"Contributor Covenant Code of Conduct","text":"members, contributors, leaders pledge make participation community harassment-free experience everyone, regardless age, body size, visible invisible disability, ethnicity, sex characteristics, gender identity expression, level experience, education, socio-economic status, nationality, personal appearance, race, caste, color, religion, sexual identity orientation. pledge act interact ways contribute open, welcoming, diverse, inclusive, healthy community.","code":""},{"path":"https://insightsengineering.github.io/cardx/CODE_OF_CONDUCT.html","id":"our-standards","dir":"","previous_headings":"","what":"Our Standards","title":"Contributor Covenant Code of Conduct","text":"Examples behavior contributes positive environment community include: Demonstrating empathy kindness toward people respectful differing opinions, viewpoints, experiences Giving gracefully accepting constructive feedback Accepting responsibility apologizing affected mistakes, learning experience Focusing best just us individuals, overall community Examples unacceptable behavior include: use sexualized language imagery, sexual attention advances kind Trolling, insulting derogatory comments, personal political attacks Public private harassment Publishing others’ private information, physical email address, without explicit permission conduct reasonably considered inappropriate professional setting","code":""},{"path":"https://insightsengineering.github.io/cardx/CODE_OF_CONDUCT.html","id":"enforcement-responsibilities","dir":"","previous_headings":"","what":"Enforcement Responsibilities","title":"Contributor Covenant Code of Conduct","text":"Community leaders responsible clarifying enforcing standards acceptable behavior take appropriate fair corrective action response behavior deem inappropriate, threatening, offensive, harmful. Community leaders right responsibility remove, edit, reject comments, commits, code, wiki edits, issues, contributions aligned Code Conduct, communicate reasons moderation decisions appropriate.","code":""},{"path":"https://insightsengineering.github.io/cardx/CODE_OF_CONDUCT.html","id":"scope","dir":"","previous_headings":"","what":"Scope","title":"Contributor Covenant Code of Conduct","text":"Code Conduct applies within community spaces, also applies individual officially representing community public spaces. Examples representing community include using official e-mail address, posting via official social media account, acting appointed representative online offline event.","code":""},{"path":"https://insightsengineering.github.io/cardx/CODE_OF_CONDUCT.html","id":"enforcement","dir":"","previous_headings":"","what":"Enforcement","title":"Contributor Covenant Code of Conduct","text":"Instances abusive, harassing, otherwise unacceptable behavior may reported community leaders responsible enforcement [INSERT CONTACT METHOD]. complaints reviewed investigated promptly fairly. community leaders obligated respect privacy security reporter incident.","code":""},{"path":"https://insightsengineering.github.io/cardx/CODE_OF_CONDUCT.html","id":"enforcement-guidelines","dir":"","previous_headings":"","what":"Enforcement Guidelines","title":"Contributor Covenant Code of Conduct","text":"Community leaders follow Community Impact Guidelines determining consequences action deem violation Code Conduct:","code":""},{"path":"https://insightsengineering.github.io/cardx/CODE_OF_CONDUCT.html","id":"id_1-correction","dir":"","previous_headings":"Enforcement Guidelines","what":"1. Correction","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Use inappropriate language behavior deemed unprofessional unwelcome community. Consequence: private, written warning community leaders, providing clarity around nature violation explanation behavior inappropriate. public apology may requested.","code":""},{"path":"https://insightsengineering.github.io/cardx/CODE_OF_CONDUCT.html","id":"id_2-warning","dir":"","previous_headings":"Enforcement Guidelines","what":"2. Warning","title":"Contributor Covenant Code of Conduct","text":"Community Impact: violation single incident series actions. Consequence: warning consequences continued behavior. interaction people involved, including unsolicited interaction enforcing Code Conduct, specified period time. includes avoiding interactions community spaces well external channels like social media. Violating terms may lead temporary permanent ban.","code":""},{"path":"https://insightsengineering.github.io/cardx/CODE_OF_CONDUCT.html","id":"id_3-temporary-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"3. Temporary Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: serious violation community standards, including sustained inappropriate behavior. Consequence: temporary ban sort interaction public communication community specified period time. public private interaction people involved, including unsolicited interaction enforcing Code Conduct, allowed period. Violating terms may lead permanent ban.","code":""},{"path":"https://insightsengineering.github.io/cardx/CODE_OF_CONDUCT.html","id":"id_4-permanent-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"4. Permanent Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Demonstrating pattern violation community standards, including sustained inappropriate behavior, harassment individual, aggression toward disparagement classes individuals. Consequence: permanent ban sort public interaction within community.","code":""},{"path":"https://insightsengineering.github.io/cardx/CODE_OF_CONDUCT.html","id":"attribution","dir":"","previous_headings":"","what":"Attribution","title":"Contributor Covenant Code of Conduct","text":"Code Conduct adapted Contributor Covenant, version 2.1, available https://www.contributor-covenant.org/version/2/1/code_of_conduct.html. Community Impact Guidelines inspired Mozilla’s code conduct enforcement ladder. answers common questions code conduct, see FAQ https://www.contributor-covenant.org/faq. Translations available https://www.contributor-covenant.org/translations.","code":""},{"path":"https://insightsengineering.github.io/cardx/CONTRIBUTING.html","id":null,"dir":"","previous_headings":"","what":"Contribution Guidelines","title":"Contribution Guidelines","text":"🙏 Thank taking time contribute! input deeply valued, whether issue, pull request, even feedback, regardless size, content scope.","code":""},{"path":"https://insightsengineering.github.io/cardx/CONTRIBUTING.html","id":"table-of-contents","dir":"","previous_headings":"","what":"Table of contents","title":"Contribution Guidelines","text":"👶 Getting started 📔 Code Conduct 🗃 License 📜 Issues 🚩 Pull requests 💻 Coding guidelines 🏆 Recognition model ❓ Questions","code":""},{"path":"https://insightsengineering.github.io/cardx/CONTRIBUTING.html","id":"getting-started","dir":"","previous_headings":"","what":"Getting started","title":"Contribution Guidelines","text":"Please refer project documentation brief introduction. Please also see articles within project documentation additional information.","code":""},{"path":"https://insightsengineering.github.io/cardx/CONTRIBUTING.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Contribution Guidelines","text":"Code Conduct governs project. Participants contributors expected follow rules outlined therein.","code":""},{"path":"https://insightsengineering.github.io/cardx/CONTRIBUTING.html","id":"license","dir":"","previous_headings":"","what":"License","title":"Contribution Guidelines","text":"contributions covered project’s license.","code":""},{"path":"https://insightsengineering.github.io/cardx/CONTRIBUTING.html","id":"issues","dir":"","previous_headings":"","what":"Issues","title":"Contribution Guidelines","text":"use GitHub track issues, feature requests, bugs. submitting new issue, please check issue already reported. issue already exists, please upvote existing issue 👍. new feature requests, please elaborate context benefit feature users, developers, relevant personas.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/cardx/CONTRIBUTING.html","id":"github-flow","dir":"","previous_headings":"Pull requests","what":"GitHub Flow","title":"Contribution Guidelines","text":"repository uses GitHub Flow model collaboration. submit pull request: Create branch Please see branch naming convention . don’t write access repository, please fork . Make changes Make sure code passes checks imposed GitHub Actions well documented well tested unit tests sufficiently covering changes introduced Create pull request (PR) pull request description, please link relevant issue (), provide detailed description change, include assumptions. Address review comments, Post approval Merge PR write access. Otherwise, reviewer merge PR behalf. Pat back Congratulations! 🎉 now official contributor project! grateful contribution.","code":""},{"path":"https://insightsengineering.github.io/cardx/CONTRIBUTING.html","id":"branch-naming-convention","dir":"","previous_headings":"Pull requests","what":"Branch naming convention","title":"Contribution Guidelines","text":"Suppose changes related current issue current project; please name branch follows: <issue_id>_<short_description>. Please use underscore (_) delimiter word separation. example, 420_fix_ui_bug suitable branch name change resolving UI-related bug reported issue number 420 current project. change affects multiple repositories, please name branches follows: <issue_id>_<issue_repo>_<short description>. example, 69_awesomeproject_fix_spelling_error reference issue 69 reported project awesomeproject aims resolve one spelling errors multiple (likely related) repositories.","code":""},{"path":"https://insightsengineering.github.io/cardx/CONTRIBUTING.html","id":"monorepo-and-stageddependencies","dir":"","previous_headings":"Pull requests","what":"monorepo and staged.dependencies","title":"Contribution Guidelines","text":"Sometimes might need change upstream dependent package(s) able submit meaningful change. using staged.dependencies functionality simulate monorepo behavior. dependency configuration already specified project’s staged_dependencies.yaml file. need name feature branches appropriately. exception branch naming convention described . Please refer staged.dependencies package documentation details.","code":""},{"path":"https://insightsengineering.github.io/cardx/CONTRIBUTING.html","id":"coding-guidelines","dir":"","previous_headings":"","what":"Coding guidelines","title":"Contribution Guidelines","text":"repository follows unified processes standards adopted maintainers ensure software development carried consistently within teams cohesively across repositories.","code":""},{"path":"https://insightsengineering.github.io/cardx/CONTRIBUTING.html","id":"style-guide","dir":"","previous_headings":"Coding guidelines","what":"Style guide","title":"Contribution Guidelines","text":"repository follows standard tidyverse style guide uses lintr lint checks. Customized lint configurations available repository’s .lintr file.","code":""},{"path":"https://insightsengineering.github.io/cardx/CONTRIBUTING.html","id":"dependency-management","dir":"","previous_headings":"Coding guidelines","what":"Dependency management","title":"Contribution Guidelines","text":"Lightweight right weight. repository follows tinyverse recommedations limiting dependencies minimum.","code":""},{"path":"https://insightsengineering.github.io/cardx/CONTRIBUTING.html","id":"dependency-version-management","dir":"","previous_headings":"Coding guidelines","what":"Dependency version management","title":"Contribution Guidelines","text":"code compatible (!) historical versions given dependenct package, required specify minimal version DESCRIPTION file. particular: development version requires (imports) development version another package - required put abc (>= 1.2.3.9000).","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/cardx/CONTRIBUTING.html","id":"r--package-versions","dir":"","previous_headings":"Coding guidelines > Recommended development environment & tools","what":"R & package versions","title":"Contribution Guidelines","text":"continuously test packages newest R version along recent dependencies CRAN BioConductor. recommend working environment also set way. can find details R version packages used R CMD check GitHub Action execution log - step prints R sessionInfo(). discover bugs older R versions older set dependencies, please create relevant bug reports.","code":""},{"path":"https://insightsengineering.github.io/cardx/CONTRIBUTING.html","id":"pre-commit","dir":"","previous_headings":"Coding guidelines > Recommended development environment & tools","what":"pre-commit","title":"Contribution Guidelines","text":"highly recommend use pre-commit tool combined R hooks pre-commit execute checks committing pushing changes. Pre-commit hooks already available repository’s .pre-commit-config.yaml file.","code":""},{"path":"https://insightsengineering.github.io/cardx/CONTRIBUTING.html","id":"recognition-model","dir":"","previous_headings":"","what":"Recognition model","title":"Contribution Guidelines","text":"mentioned previously, contributions deeply valued appreciated. contribution data available part repository insights, recognize significant contribution hence add contributor package authors list, following rules enforced: Minimum 5% lines code authored* (determined git blame query) top 5 contributors terms number commits lines added lines removed* *Excluding auto-generated code, including limited roxygen comments renv.lock files. package maintainer also reserves right adjust criteria recognize contributions.","code":""},{"path":"https://insightsengineering.github.io/cardx/CONTRIBUTING.html","id":"questions","dir":"","previous_headings":"","what":"Questions","title":"Contribution Guidelines","text":"questions regarding contribution guidelines, please contact package/repository maintainer.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/cardx/SECURITY.html","id":"reporting-security-issues","dir":"","previous_headings":"","what":"Reporting Security Issues","title":"Security Policy","text":"believe found security vulnerability repositories organization, please report us coordinated disclosure. Please report security vulnerabilities public GitHub issues, discussions, pull requests. Instead, please send email vulnerability.management[@]roche.com. Please include much information listed can help us better understand resolve issue: type issue (e.g., buffer overflow, SQL injection, cross-site scripting) Full paths source file(s) related manifestation issue location affected source code (tag/branch/commit direct URL) special configuration required reproduce issue Step--step instructions reproduce issue Proof--concept exploit code (possible) Impact issue, including attacker might exploit issue information help us triage report quickly.","code":""},{"path":"https://insightsengineering.github.io/cardx/SECURITY.html","id":"data-security-standards-dss","dir":"","previous_headings":"","what":"Data Security Standards (DSS)","title":"Security Policy","text":"Please make sure reporting issues form bug, feature, pull request, sensitive information PII, PHI, PCI completely removed text attachments, including pictures videos.","code":""},{"path":"https://insightsengineering.github.io/cardx/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Daniel Sjoberg. Author, maintainer. Abinaya Yogasekaram. Author. Emily de la Rua. Author. F. Hoffmann-La Roche AG. Copyright holder, funder.","code":""},{"path":"https://insightsengineering.github.io/cardx/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Sjoberg D, Yogasekaram , de la Rua E (2024). cardx: Extra Analysis Results Data Utilities. R package version 0.1.0.9026, https://github.com/insightsengineering/cardx.","code":"@Manual{,   title = {cardx: Extra Analysis Results Data Utilities},   author = {Daniel Sjoberg and Abinaya Yogasekaram and Emily {de la Rua}},   year = {2024},   note = {R package version 0.1.0.9026},   url = {https://github.com/insightsengineering/cardx}, }"},{"path":"https://insightsengineering.github.io/cardx/index.html","id":"cardx-","dir":"","previous_headings":"","what":"Extra Analysis Results Data Utilities","title":"Extra Analysis Results Data Utilities","text":"source repository cardx R package.","code":""},{"path":"https://insightsengineering.github.io/cardx/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Extra Analysis Results Data Utilities","text":"latest development version cardx can directly installed GitHub running following:","code":"if (!require(\"pak\")) install.packages(\"pak\") pak::pak(\"insightsengineering/cardx\")"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_aod_wald_test.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Wald Test — ard_aod_wald_test","title":"ARD Wald Test — ard_aod_wald_test","text":"Function takes regression model object calculates Wald statistical test using aod::wald.test().","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_aod_wald_test.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Wald Test — ard_aod_wald_test","text":"","code":"ard_aod_wald_test(x, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_aod_wald_test.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Wald Test — ard_aod_wald_test","text":"x regression model object ... arguments passed aod::wald.test(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_aod_wald_test.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Wald Test — ard_aod_wald_test","text":"data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_aod_wald_test.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Wald Test — ard_aod_wald_test","text":"","code":"lm(AGE ~ ARM, data = cards::ADSL) |>   ard_aod_wald_test() #> {cards} data frame: 6 x 8 #>      variable   context stat_name stat_label     stat fmt_fn #> 1 (Intercept) aod_wald…        df  Degrees …        1      1 #> 2 (Intercept) aod_wald… statistic  Statistic 7126.713      1 #> 3 (Intercept) aod_wald…   p.value    p-value        0      1 #> 4         ARM aod_wald…        df  Degrees …        2      1 #> 5         ARM aod_wald… statistic  Statistic    1.046      1 #> 6         ARM aod_wald…   p.value    p-value    0.593      1 #> ℹ 2 more variables: warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_car_anova.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD ANOVA from car Package — ard_car_anova","title":"ARD ANOVA from car Package — ard_car_anova","text":"Function takes regression model object calculated ANOVA using car::Anova().","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_car_anova.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD ANOVA from car Package — ard_car_anova","text":"","code":"ard_car_anova(x, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_car_anova.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD ANOVA from car Package — ard_car_anova","text":"x regression model object ... arguments passed car::Anova(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_car_anova.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD ANOVA from car Package — ard_car_anova","text":"data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_car_anova.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD ANOVA from car Package — ard_car_anova","text":"","code":"lm(AGE ~ ARM, data = cards::ADSL) |>   ard_car_anova() #> {cards} data frame: 5 x 8 #>   variable   context stat_name stat_label   stat fmt_fn #> 1      ARM car_anova     sumsq      sumsq 71.386      1 #> 2      ARM car_anova        df  Degrees …      2      1 #> 3      ARM car_anova    meansq     meansq 35.693      1 #> 4      ARM car_anova statistic  Statistic  0.523      1 #> 5      ARM car_anova   p.value    p-value  0.593      1 #> ℹ 2 more variables: warning, error  glm(vs ~ factor(cyl) + factor(am), data = mtcars, family = binomial) |>   ard_car_anova(test.statistic = \"Wald\") #> {cards} data frame: 6 x 8 #>      variable   context stat_name stat_label  stat   warning #> 1 factor(cyl) car_anova statistic  Statistic     0 glm.fit:… #> 2 factor(cyl) car_anova        df  Degrees …     2 glm.fit:… #> 3 factor(cyl) car_anova   p.value    p-value     1 glm.fit:… #> 4  factor(am) car_anova statistic  Statistic     0 glm.fit:… #> 5  factor(am) car_anova        df  Degrees …     1 glm.fit:… #> 6  factor(am) car_anova   p.value    p-value 0.998 glm.fit:… #> ℹ 2 more variables: fmt_fn, error"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_car_vif.html","id":null,"dir":"Reference","previous_headings":"","what":"Regression VIF ARD — ard_car_vif","title":"Regression VIF ARD — ard_car_vif","text":"Function takes regression model object returns variance inflation factor (VIF) using car::vif() converts ARD structure","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_car_vif.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Regression VIF ARD — ard_car_vif","text":"","code":"ard_car_vif(x, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_car_vif.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Regression VIF ARD — ard_car_vif","text":"x regression model object See car::vif() details ... arguments passed car::vif(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_car_vif.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Regression VIF ARD — ard_car_vif","text":"data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_car_vif.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Regression VIF ARD — ard_car_vif","text":"","code":"lm(AGE ~ ARM + SEX, data = cards::ADSL) |>   ard_car_vif() #> {cards} data frame: 6 x 8 #>   variable context stat_name stat_label  stat fmt_fn #> 1      ARM car_vif      GVIF       GVIF 1.016      1 #> 2      ARM car_vif        df         df     2      1 #> 3      ARM car_vif     aGVIF  Adjusted… 1.004      1 #> 4      SEX car_vif      GVIF       GVIF 1.016      1 #> 5      SEX car_vif        df         df     1      1 #> 6      SEX car_vif     aGVIF  Adjusted… 1.008      1 #> ℹ 2 more variables: warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_effectsize_cohens_d.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Cohen's D Test — ard_effectsize_cohens_d","title":"ARD Cohen's D Test — ard_effectsize_cohens_d","text":"Analysis results data paired non-paired Cohen's D Effect Size Test using effectsize::cohens_d().","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_effectsize_cohens_d.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Cohen's D Test — ard_effectsize_cohens_d","text":"","code":"ard_effectsize_cohens_d(data, by, variables, ...)  ard_effectsize_paired_cohens_d(data, by, variables, id, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_effectsize_cohens_d.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Cohen's D Test — ard_effectsize_cohens_d","text":"data (data.frame) data frame. See details. (tidy-select) column name compare . Must categorical variable exactly two levels. variables (tidy-select) column names compared. Must continuous variables. Independent tests run variable. ... arguments passed effectsize::cohens_d(...) id (tidy-select) column name subject participant ID","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_effectsize_cohens_d.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Cohen's D Test — ard_effectsize_cohens_d","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_effectsize_cohens_d.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"ARD Cohen's D Test — ard_effectsize_cohens_d","text":"ard_effectsize_cohens_d() function, data expected one row per subject. data passed effectsize::cohens_d(data[[variable]]~data[[]], data, paired = FALSE, ...). ard_effectsize_paired_cohens_d() function, data expected one row per subject per level. effect size calculated, data reshaped wide format one row per subject. data passed effectsize::cohens_d(x = data_wide[[<level 1>]], y = data_wide[[<level 2>]], paired = TRUE, ...).","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_effectsize_cohens_d.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Cohen's D Test — ard_effectsize_cohens_d","text":"","code":"cards::ADSL |>   dplyr::filter(ARM %in% c(\"Placebo\", \"Xanomeline High Dose\")) |>   ard_effectsize_cohens_d(by = ARM, variables = AGE) #> {cards} data frame: 8 x 9 #>   group1 variable   context   stat_name stat_label      stat #> 1    ARM      AGE effectsi…    estimate  Effect S…       0.1 #> 2    ARM      AGE effectsi…  conf.level  CI Confi…      0.95 #> 3    ARM      AGE effectsi…    conf.low  CI Lower…    -0.201 #> 4    ARM      AGE effectsi…   conf.high  CI Upper…     0.401 #> 5    ARM      AGE effectsi…          mu    H0 Mean         0 #> 6    ARM      AGE effectsi…      paired  Paired t…     FALSE #> 7    ARM      AGE effectsi…   pooled_sd  Pooled S…      TRUE #> 8    ARM      AGE effectsi… alternative  Alternat… two.sided #> ℹ 3 more variables: fmt_fn, warning, error  # constructing a paired data set, # where patients receive both treatments cards::ADSL[c(\"ARM\", \"AGE\")] |>   dplyr::filter(ARM %in% c(\"Placebo\", \"Xanomeline High Dose\")) |>   dplyr::mutate(.by = ARM, USUBJID = dplyr::row_number()) |>   dplyr::arrange(USUBJID, ARM) |>   dplyr::group_by(USUBJID) |>   dplyr::filter(dplyr::n() > 1) |>   ard_effectsize_paired_cohens_d(by = ARM, variables = AGE, id = USUBJID) #> {cards} data frame: 8 x 9 #>   group1 variable   context   stat_name stat_label      stat #> 1    ARM      AGE effectsi…    estimate  Effect S…     0.069 #> 2    ARM      AGE effectsi…  conf.level  CI Confi…      0.95 #> 3    ARM      AGE effectsi…    conf.low  CI Lower…    -0.146 #> 4    ARM      AGE effectsi…   conf.high  CI Upper…     0.282 #> 5    ARM      AGE effectsi…          mu    H0 Mean         0 #> 6    ARM      AGE effectsi…      paired  Paired t…      TRUE #> 7    ARM      AGE effectsi…   pooled_sd  Pooled S…      TRUE #> 8    ARM      AGE effectsi… alternative  Alternat… two.sided #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_effectsize_hedges_g.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Hedge's G Test — ard_effectsize_hedges_g","title":"ARD Hedge's G Test — ard_effectsize_hedges_g","text":"Analysis results data paired non-paired Hedge's G Effect Size Test using effectsize::hedges_g().","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_effectsize_hedges_g.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Hedge's G Test — ard_effectsize_hedges_g","text":"","code":"ard_effectsize_hedges_g(data, by, variables, ...)  ard_effectsize_paired_hedges_g(data, by, variables, id, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_effectsize_hedges_g.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Hedge's G Test — ard_effectsize_hedges_g","text":"data (data.frame) data frame. See details. (tidy-select) column name compare . Must categorical variable exactly two levels. variables (tidy-select) column names compared. Must continuous variable. Independent tests run variable ... arguments passed effectsize::hedges_g(...) id (tidy-select) column name subject participant ID","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_effectsize_hedges_g.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Hedge's G Test — ard_effectsize_hedges_g","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_effectsize_hedges_g.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"ARD Hedge's G Test — ard_effectsize_hedges_g","text":"ard_effectsize_hedges_g() function, data expected one row per subject. data passed effectsize::hedges_g(data[[variable]]~data[[]], data, paired = FALSE, ...). ard_effectsize_paired_hedges_g() function, data expected one row per subject per level. effect size calculated, data reshaped wide format one row per subject. data passed effectsize::hedges_g(x = data_wide[[<level 1>]], y = data_wide[[<level 2>]], paired = TRUE, ...).","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_effectsize_hedges_g.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Hedge's G Test — ard_effectsize_hedges_g","text":"","code":"cards::ADSL |>   dplyr::filter(ARM %in% c(\"Placebo\", \"Xanomeline High Dose\")) |>   ard_effectsize_hedges_g(by = ARM, variables = AGE) #> {cards} data frame: 8 x 9 #>   group1 variable   context   stat_name stat_label      stat #> 1    ARM      AGE effectsi…    estimate  Effect S…       0.1 #> 2    ARM      AGE effectsi…  conf.level  CI Confi…      0.95 #> 3    ARM      AGE effectsi…    conf.low  CI Lower…      -0.2 #> 4    ARM      AGE effectsi…   conf.high  CI Upper…     0.399 #> 5    ARM      AGE effectsi…          mu    H0 Mean         0 #> 6    ARM      AGE effectsi…      paired  Paired t…     FALSE #> 7    ARM      AGE effectsi…   pooled_sd  Pooled S…      TRUE #> 8    ARM      AGE effectsi… alternative  Alternat… two.sided #> ℹ 3 more variables: fmt_fn, warning, error  # constructing a paired data set, # where patients receive both treatments cards::ADSL[c(\"ARM\", \"AGE\")] |>   dplyr::filter(ARM %in% c(\"Placebo\", \"Xanomeline High Dose\")) |>   dplyr::mutate(.by = ARM, USUBJID = dplyr::row_number()) |>   dplyr::arrange(USUBJID, ARM) |>   dplyr::group_by(USUBJID) |>   dplyr::filter(dplyr::n() > 1) |>   ard_effectsize_paired_hedges_g(by = ARM, variables = AGE, id = USUBJID) #> {cards} data frame: 8 x 9 #>   group1 variable   context   stat_name stat_label      stat #> 1    ARM      AGE effectsi…    estimate  Effect S…     0.068 #> 2    ARM      AGE effectsi…  conf.level  CI Confi…      0.95 #> 3    ARM      AGE effectsi…    conf.low  CI Lower…    -0.144 #> 4    ARM      AGE effectsi…   conf.high  CI Upper…      0.28 #> 5    ARM      AGE effectsi…          mu    H0 Mean         0 #> 6    ARM      AGE effectsi…      paired  Paired t…      TRUE #> 7    ARM      AGE effectsi…   pooled_sd  Pooled S…      TRUE #> 8    ARM      AGE effectsi… alternative  Alternat… two.sided #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_emmeans_mean_difference.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD for LS Mean Difference — ard_emmeans_mean_difference","title":"ARD for LS Mean Difference — ard_emmeans_mean_difference","text":"function calculates least-squares mean differences using 'emmeans' package using following   arguments data, formula, method, method.args, package used construct regression model via cardx::construct_model().","code":"emmeans::emmeans(object = <regression model>, specs = ~ <primary covariate>) |>   emmeans::contrast(method = \"pairwise\") |>   summary(infer = TRUE, level = <confidence level>)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_emmeans_mean_difference.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD for LS Mean Difference — ard_emmeans_mean_difference","text":"","code":"ard_emmeans_mean_difference(   data,   formula,   method,   method.args = list(),   package = \"base\",   response_type = c(\"continuous\", \"dichotomous\"),   conf.level = 0.95,   primary_covariate = getElement(attr(stats::terms(formula), \"term.labels\"), 1L) )"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_emmeans_mean_difference.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD for LS Mean Difference — ard_emmeans_mean_difference","text":"data (data.frame/survey.design) data frame survey design object formula (formula) formula method (string) string naming function called, e.g. \"glm\". function belongs library attached, package name must specified package argument. method.args (named list) named list arguments passed fn. package (string) string package name temporarily loaded function specified method executed. response_type (string) string indicating whether model outcome 'continuous' 'dichotomous'. 'dichotomous', call emmeans::emmeans() supplemented argument regrid=\"response\". conf.level (scalar numeric) confidence level confidence interval. Default 0.95. primary_covariate (string) string indicating primary covariate (typically dichotomous treatment variable). Default first covariate listed formula.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_emmeans_mean_difference.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD for LS Mean Difference — ard_emmeans_mean_difference","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_emmeans_mean_difference.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD for LS Mean Difference — ard_emmeans_mean_difference","text":"","code":"ard_emmeans_mean_difference(   data = mtcars,   formula = mpg ~ am + cyl,   method = \"lm\" ) #> {cards} data frame: 8 x 10 #>   group1 variable variable_level  stat_name stat_label      stat #> 1     am contrast      am0 - am1   estimate  Mean Dif…    -2.567 #> 2     am contrast      am0 - am1  std.error  std.error     1.291 #> 3     am contrast      am0 - am1         df         df        29 #> 4     am contrast      am0 - am1   conf.low  CI Lower…    -5.208 #> 5     am contrast      am0 - am1  conf.high  CI Upper…     0.074 #> 6     am contrast      am0 - am1    p.value    p-value     0.056 #> 7     am contrast      am0 - am1 conf.level  CI Confi…      0.95 #> 8     am contrast      am0 - am1     method     method Least-sq… #> ℹ 4 more variables: context, fmt_fn, warning, error  ard_emmeans_mean_difference(   data = mtcars,   formula = vs ~ am + mpg,   method = \"glm\",   method.args = list(family = binomial),   response_type = \"dichotomous\" ) #> {cards} data frame: 8 x 10 #>   group1 variable variable_level  stat_name stat_label      stat #> 1     am contrast      am0 - am1   estimate  Mean Dif…      0.61 #> 2     am contrast      am0 - am1  std.error  std.error     0.229 #> 3     am contrast      am0 - am1         df         df       Inf #> 4     am contrast      am0 - am1   conf.low  CI Lower…     0.162 #> 5     am contrast      am0 - am1  conf.high  CI Upper…     1.059 #> 6     am contrast      am0 - am1    p.value    p-value     0.008 #> 7     am contrast      am0 - am1 conf.level  CI Confi…      0.95 #> 8     am contrast      am0 - am1     method     method Least-sq… #> ℹ 4 more variables: context, fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_proportion_ci.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Proportion Confidence Intervals — ard_proportion_ci","title":"ARD Proportion Confidence Intervals — ard_proportion_ci","text":"Calculate confidence intervals proportions.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_proportion_ci.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Proportion Confidence Intervals — ard_proportion_ci","text":"","code":"ard_proportion_ci(   data,   variables,   by = dplyr::group_vars(data),   conf.level = 0.95,   strata,   weights = NULL,   max.iterations = 10,   method = c(\"waldcc\", \"wald\", \"clopper-pearson\", \"wilson\", \"wilsoncc\", \"strat_wilson\",     \"strat_wilsoncc\", \"agresti-coull\", \"jeffreys\") )"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_proportion_ci.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Proportion Confidence Intervals — ard_proportion_ci","text":"data (data.frame) data frame variables (tidy-select) columns include summaries. Columns must class <logical> <numeric> values coded c(0, 1). (tidy-select) columns stratify calculations conf.level (numeric) scalar (0, 1) indicating confidence level. Default 0.95 strata, weights, max.iterations arguments passed proportion_ci_strat_wilson(), method='strat_wilson' method (string) string indicating type confidence interval calculate. Must one 'waldcc', 'wald', 'clopper-pearson', 'wilson', 'wilsoncc', 'strat_wilson', 'strat_wilsoncc', 'agresti-coull', 'jeffreys'. See ?proportion_ci details.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_proportion_ci.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Proportion Confidence Intervals — ard_proportion_ci","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_proportion_ci.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Proportion Confidence Intervals — ard_proportion_ci","text":"","code":"ard_proportion_ci(mtcars, variables = c(vs, am), method = \"wilson\") #> {cards} data frame: 20 x 8 #>    variable   context   stat_name stat_label      stat fmt_fn #> 1        vs proporti…           N          N        32      0 #> 2        vs proporti…  conf.level  conf.lev…      0.95      1 #> 3        vs proporti…    estimate   estimate     0.438      1 #> 4        vs proporti…   statistic  statistic       0.5      1 #> 5        vs proporti…     p.value    p.value      0.48      1 #> 6        vs proporti…   parameter  parameter         1      0 #> 7        vs proporti…    conf.low   conf.low     0.282      1 #> 8        vs proporti…   conf.high  conf.high     0.607      1 #> 9        vs proporti…      method     method Wilson C…   <fn> #> 10       vs proporti… alternative  alternat… two.sided   <fn> #> 11       am proporti…           N          N        32      0 #> 12       am proporti…  conf.level  conf.lev…      0.95      1 #> 13       am proporti…    estimate   estimate     0.406      1 #> 14       am proporti…   statistic  statistic     1.125      1 #> 15       am proporti…     p.value    p.value     0.289      1 #> 16       am proporti…   parameter  parameter         1      0 #> 17       am proporti…    conf.low   conf.low     0.255      1 #> 18       am proporti…   conf.high  conf.high     0.577      1 #> 19       am proporti…      method     method Wilson C…   <fn> #> 20       am proporti… alternative  alternat… two.sided   <fn> #> ℹ 2 more variables: warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_regression.html","id":null,"dir":"Reference","previous_headings":"","what":"Regression ARD — ard_regression","title":"Regression ARD — ard_regression","text":"Function takes regression model object converts ARD structure using broom.helpers package.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_regression.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Regression ARD — ard_regression","text":"","code":"ard_regression(x, ...)  # S3 method for default ard_regression(x, tidy_fun = broom.helpers::tidy_with_broom_or_parameters, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_regression.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Regression ARD — ard_regression","text":"x regression model object ... Arguments passed broom.helpers::tidy_plus_plus() tidy_fun (function) tidier. Default broom.helpers::tidy_with_broom_or_parameters","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_regression.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Regression ARD — ard_regression","text":"data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_regression.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Regression ARD — ard_regression","text":"","code":"lm(AGE ~ ARM, data = cards::ADSL) |>   ard_regression(add_estimate_to_reference_rows = TRUE) #> {cards} data frame: 43 x 7 #>    variable variable_level   context      stat_name stat_label      stat #> 1       ARM        Placebo regressi…           term       term ARMPlace… #> 2       ARM        Placebo regressi…      var_label      Label Descript… #> 3       ARM        Placebo regressi…      var_class      Class character #> 4       ARM        Placebo regressi…       var_type       Type categori… #> 5       ARM        Placebo regressi…    var_nlevels   N Levels         3 #> 6       ARM        Placebo regressi…      contrasts  contrasts contr.tr… #> 7       ARM        Placebo regressi… contrasts_type  Contrast… treatment #> 8       ARM        Placebo regressi…  reference_row  referenc…      TRUE #> 9       ARM        Placebo regressi…          label  Level La…   Placebo #> 10      ARM        Placebo regressi…          n_obs     N Obs.        86 #> ℹ 33 more rows #> ℹ Use `print(n = ...)` to see more rows #> ℹ 1 more variable: fmt_fn"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_regression_basic.html","id":null,"dir":"Reference","previous_headings":"","what":"Basic Regression ARD — ard_regression_basic","title":"Basic Regression ARD — ard_regression_basic","text":"function takes regression model provides basic statistics ARD structure. default output simpler ard_regression(). function primarily matches regression terms underlying variable names levels. default arguments used ","code":"broom.helpers::tidy_plus_plus(   add_reference_rows = FALSE,   add_estimate_to_reference_rows = FALSE,   add_n = FALSE,   intercept = FALSE )"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_regression_basic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Basic Regression ARD — ard_regression_basic","text":"","code":"ard_regression_basic(   x,   tidy_fun = broom.helpers::tidy_with_broom_or_parameters,   stats_to_remove = c(\"term\", \"var_type\", \"var_label\", \"var_class\", \"label\",     \"contrasts_type\", \"contrasts\", \"var_nlevels\"),   ... )"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_regression_basic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Basic Regression ARD — ard_regression_basic","text":"x regression model object tidy_fun (function) tidier. Default broom.helpers::tidy_with_broom_or_parameters stats_to_remove (character) character vector statistic names remove. Default c(\"term\", \"var_type\", \"var_label\", \"var_class\", \"label\", \"contrasts_type\", \"contrasts\", \"var_nlevels\"). ... Arguments passed broom.helpers::tidy_plus_plus()","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_regression_basic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Basic Regression ARD — ard_regression_basic","text":"data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_regression_basic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Basic Regression ARD — ard_regression_basic","text":"","code":"lm(AGE ~ ARM, data = cards::ADSL) |>   ard_regression_basic() #> {cards} data frame: 12 x 7 #>    variable variable_level   context stat_name stat_label   stat #> 1       ARM      Xanomeli… regressi…  estimate  Coeffici… -0.828 #> 2       ARM      Xanomeli… regressi… std.error  Standard…  1.267 #> 3       ARM      Xanomeli… regressi… statistic  statistic -0.654 #> 4       ARM      Xanomeli… regressi…   p.value    p-value  0.514 #> 5       ARM      Xanomeli… regressi…  conf.low  CI Lower… -3.324 #> 6       ARM      Xanomeli… regressi… conf.high  CI Upper…  1.668 #> 7       ARM      Xanomeli… regressi…  estimate  Coeffici…  0.457 #> 8       ARM      Xanomeli… regressi… std.error  Standard…  1.267 #> 9       ARM      Xanomeli… regressi… statistic  statistic  0.361 #> 10      ARM      Xanomeli… regressi…   p.value    p-value  0.719 #> 11      ARM      Xanomeli… regressi…  conf.low  CI Lower… -2.039 #> 12      ARM      Xanomeli… regressi… conf.high  CI Upper…  2.953 #> ℹ 1 more variable: fmt_fn"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_smd_smd.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Standardized Mean Difference — ard_smd_smd","title":"ARD Standardized Mean Difference — ard_smd_smd","text":"Standardized mean difference calculated via smd::smd() na.rm = TRUE.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_smd_smd.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Standardized Mean Difference — ard_smd_smd","text":"","code":"ard_smd_smd(data, by, variables, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_smd_smd.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Standardized Mean Difference — ard_smd_smd","text":"data (data.frame/survey.design) data frame object class 'survey.design' (typically created survey::svydesign()). (tidy-select) column name compare . variables (tidy-select) column names compared. Independent tests computed variable. ... Arguments passed smd::smd std.error Logical indicator computing standard errors using compute_smd_var. Defaults FALSE. gref integer indicating level g use reference group. Defaults 1.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_smd_smd.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Standardized Mean Difference — ard_smd_smd","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_smd_smd.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Standardized Mean Difference — ard_smd_smd","text":"","code":"ard_smd_smd(cards::ADSL, by = ARM, variables = AGE, std.error = TRUE) #> {cards} data frame: 3 x 9 #>   group1 variable context stat_name stat_label          stat #> 1    ARM      AGE smd_smd  estimate  Standard… 0.101, -0.055 #> 2    ARM      AGE smd_smd std.error  Standard…  0.154, 0.153 #> 3    ARM      AGE smd_smd      gref  Integer …             1 #> ℹ 3 more variables: fmt_fn, warning, error ard_smd_smd(cards::ADSL, by = ARM, variables = AGEGR1, std.error = TRUE) #> {cards} data frame: 3 x 9 #>   group1 variable context stat_name stat_label         stat #> 1    ARM   AGEGR1 smd_smd  estimate  Standard… 0.351, 0.214 #> 2    ARM   AGEGR1 smd_smd std.error  Standard… 0.155, 0.154 #> 3    ARM   AGEGR1 smd_smd      gref  Integer …            1 #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_anova.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD ANOVA — ard_stats_anova","title":"ARD ANOVA — ard_stats_anova","text":"Prepare ANOVA results stats::anova() function. Users may pass pre-calculated stats::anova() object list formulas. latter case, models constructed using information passed models passed stats::anova().","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_anova.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD ANOVA — ard_stats_anova","text":"","code":"ard_stats_anova(x, ...)  # S3 method for anova ard_stats_anova(x, method_text = \"ANOVA results from `stats::anova()`\", ...)  # S3 method for data.frame ard_stats_anova(   x,   formulas,   method,   method.args = list(),   package = \"base\",   method_text = \"ANOVA results from `stats::anova()`\",   ... )"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_anova.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD ANOVA — ard_stats_anova","text":"x (anova data.frame) object class 'anova' created stats::anova() data frame ... dots future extensions must empty. method_text (string) string method used. Default \"ANOVA results stats::anova()\". provide option change stats::anova() can produce results many types models may warrant precise description. formulas (list) list formulas method (string) string naming function called, e.g. \"glm\". function belongs library attached, package name must specified package argument. method.args (named list) named list arguments passed fn. package (string) string package name temporarily loaded function specified method executed.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_anova.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD ANOVA — ard_stats_anova","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_anova.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"ARD ANOVA — ard_stats_anova","text":"list formulas supplied ard_stats_anova(), formulas along information arguments, used construct models pass models stats::anova(). models constructed using rlang::exec(), similar .call().   function executed withr::with_namespace(package), allows use ard_stats_anova(method) packages, e.g. package = 'lme4' must specified method = 'glmer'. See example .","code":"rlang::exec(.fn = method, formula = formula, data = data, !!!method.args)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_anova.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD ANOVA — ard_stats_anova","text":"","code":"anova(   lm(mpg ~ am, mtcars),   lm(mpg ~ am + hp, mtcars) ) |>   ard_stats_anova() #> {cards} data frame: 11 x 8 #>    variable   context   stat_name stat_label      stat fmt_fn #> 1   model_1 stats_an…        term       term  mpg ~ am   NULL #> 2   model_1 stats_an… df.residual  df for r…        30      1 #> 3   model_1 stats_an…         rss  Residual…   720.897      1 #> 4   model_2 stats_an…        term       term mpg ~ am…   NULL #> 5   model_2 stats_an… df.residual  df for r…        29      1 #> 6   model_2 stats_an…         rss  Residual…   245.439      1 #> 7   model_2 stats_an…          df  Degrees …         1      1 #> 8   model_2 stats_an…       sumsq  Sum of S…   475.457      1 #> 9   model_2 stats_an…   statistic  statistic    56.178      1 #> 10  model_2 stats_an…     p.value    p-value         0      1 #> 11  model_2 stats_an…      method     method ANOVA re…   NULL #> ℹ 2 more variables: warning, error  ard_stats_anova(   x = mtcars,   formulas = list(am ~ mpg, am ~ mpg + hp),   method = \"glm\",   method.args = list(family = binomial) ) #> {cards} data frame: 9 x 8 #>   variable   context         stat_name stat_label      stat fmt_fn #> 1  model_1 stats_an…              term       term  am ~ mpg   NULL #> 2  model_1 stats_an…       df.residual  df for r…        30      1 #> 3  model_1 stats_an… residual.deviance  residual…    29.675      1 #> 4  model_2 stats_an…              term       term am ~ mpg…   NULL #> 5  model_2 stats_an…       df.residual  df for r…        29      1 #> 6  model_2 stats_an… residual.deviance  residual…    19.233      1 #> 7  model_2 stats_an…                df  Degrees …         1      1 #> 8  model_2 stats_an…          deviance   deviance    10.443      1 #> 9  model_2 stats_an…            method     method ANOVA re…   NULL #> ℹ 2 more variables: warning, error  ard_stats_anova(   x = mtcars,   formulas = list(am ~ 1 + (1 | vs), am ~ mpg + (1 | vs)),   method = \"glmer\",   method.args = list(family = binomial),   package = \"lme4\" ) #> {cards} data frame: 16 x 8 #>    variable   context stat_name stat_label      stat   warning #> 1   model_1 stats_an…      term       term    MODEL1 failed t… #> 2   model_1 stats_an…      npar       npar         2 failed t… #> 3   model_1 stats_an…       AIC        AIC     47.23 failed t… #> 4   model_1 stats_an…       BIC        BIC    50.161 failed t… #> 5   model_1 stats_an…    logLik     logLik   -21.615 failed t… #> 6   model_1 stats_an…  deviance   deviance     43.23 failed t… #> 7   model_2 stats_an…      term       term    MODEL2 failed t… #> 8   model_2 stats_an…      npar       npar         3 failed t… #> 9   model_2 stats_an…       AIC        AIC     35.25 failed t… #> 10  model_2 stats_an…       BIC        BIC    39.647 failed t… #> 11  model_2 stats_an…    logLik     logLik   -14.625 failed t… #> 12  model_2 stats_an…  deviance   deviance     29.25 failed t… #> 13  model_2 stats_an… statistic  statistic    13.979 failed t… #> 14  model_2 stats_an…        df  Degrees …         1 failed t… #> 15  model_2 stats_an…   p.value    p-value         0 failed t… #> 16  model_2 stats_an…    method     method ANOVA re… failed t… #> ℹ 2 more variables: fmt_fn, error"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_aov.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD ANOVA — ard_stats_aov","title":"ARD ANOVA — ard_stats_aov","text":"Analysis results data Analysis Variance. Calculated stats::aov()","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_aov.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD ANOVA — ard_stats_aov","text":"","code":"ard_stats_aov(formula, data, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_aov.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD ANOVA — ard_stats_aov","text":"formula formula specifying model. data data frame variables specified     formula found. missing, variables searched     standard way. ... arguments passed stats::aov(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_aov.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD ANOVA — ard_stats_aov","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_aov.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD ANOVA — ard_stats_aov","text":"","code":"ard_stats_aov(AGE ~ ARM, data = cards::ADSL) #> {cards} data frame: 5 x 7 #>   variable   context stat_name stat_label   stat error #> 1      ARM stats_aov     sumsq  Sum of S… 71.386       #> 2      ARM stats_aov        df  Degrees …      2       #> 3      ARM stats_aov    meansq  Mean of … 35.693       #> 4      ARM stats_aov statistic  Statistic  0.523       #> 5      ARM stats_aov   p.value    p-value  0.593       #> ℹ 1 more variable: warning"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_chisq_test.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Chi-squared Test — ard_stats_chisq_test","title":"ARD Chi-squared Test — ard_stats_chisq_test","text":"Analysis results data Pearson's Chi-squared Test. Calculated chisq.test(x = data[[variable]], y = data[[]], ...)","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_chisq_test.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Chi-squared Test — ard_stats_chisq_test","text":"","code":"ard_stats_chisq_test(data, by, variables, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_chisq_test.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Chi-squared Test — ard_stats_chisq_test","text":"data (data.frame) data frame. (tidy-select) column name compare . variables (tidy-select) column names compared. Independent tests computed variable. ... additional arguments passed chisq.test(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_chisq_test.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Chi-squared Test — ard_stats_chisq_test","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_chisq_test.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Chi-squared Test — ard_stats_chisq_test","text":"","code":"cards::ADSL |>   ard_stats_chisq_test(by = \"ARM\", variables = \"AGEGR1\") #> {cards} data frame: 9 x 9 #>   group1 variable   context        stat_name stat_label #> 1    ARM   AGEGR1 stats_ch…        statistic  X-square… #> 2    ARM   AGEGR1 stats_ch…          p.value    p-value #> 3    ARM   AGEGR1 stats_ch…        parameter  Degrees … #> 4    ARM   AGEGR1 stats_ch…           method     method #> 5    ARM   AGEGR1 stats_ch…          correct    correct #> 6    ARM   AGEGR1 stats_ch…                p          p #> 7    ARM   AGEGR1 stats_ch…        rescale.p  rescale.p #> 8    ARM   AGEGR1 stats_ch… simulate.p.value  simulate… #> 9    ARM   AGEGR1 stats_ch…                B          B #>                          stat #> 1                       6.852 #> 2                       0.144 #> 3                           4 #> 4                   Pearson'… #> 5                        TRUE #> 6 rep, 1/length(x), length(x) #> 7                       FALSE #> 8                       FALSE #> 9                        2000 #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_fisher_test.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Fisher's Exact Test — ard_stats_fisher_test","title":"ARD Fisher's Exact Test — ard_stats_fisher_test","text":"Analysis results data Fisher's Exact Test. Calculated fisher.test(x = data[[variable]], y = data[[]], ...)","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_fisher_test.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Fisher's Exact Test — ard_stats_fisher_test","text":"","code":"ard_stats_fisher_test(data, by, variables, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_fisher_test.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Fisher's Exact Test — ard_stats_fisher_test","text":"data (data.frame) data frame. (tidy-select) column name compare variables (tidy-select) column names compared. Independent tests computed variable. ... additional arguments passed fisher.test(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_fisher_test.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Fisher's Exact Test — ard_stats_fisher_test","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_fisher_test.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Fisher's Exact Test — ard_stats_fisher_test","text":"","code":"cards::ADSL[1:30, ] |>   ard_stats_fisher_test(by = \"ARM\", variables = \"AGEGR1\") #> {cards} data frame: 12 x 9 #>    group1 variable   context        stat_name stat_label        stat #> 1     ARM   AGEGR1 stats_fi…          p.value    p-value       0.089 #> 2     ARM   AGEGR1 stats_fi…           method     method   Fisher's… #> 3     ARM   AGEGR1 stats_fi…      alternative  alternat…   two.sided #> 4     ARM   AGEGR1 stats_fi…        workspace  workspace       2e+05 #> 5     ARM   AGEGR1 stats_fi…           hybrid     hybrid       FALSE #> 6     ARM   AGEGR1 stats_fi…       hybridPars  hybridPa… c, 5, 80, 1 #> 7     ARM   AGEGR1 stats_fi…          control    control        list #> 8     ARM   AGEGR1 stats_fi…               or         or           1 #> 9     ARM   AGEGR1 stats_fi…         conf.int   conf.int        TRUE #> 10    ARM   AGEGR1 stats_fi…       conf.level  conf.lev…        0.95 #> 11    ARM   AGEGR1 stats_fi… simulate.p.value  simulate…       FALSE #> 12    ARM   AGEGR1 stats_fi…                B          B        2000 #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_kruskal_test.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Kruskal-Wallis Test — ard_stats_kruskal_test","title":"ARD Kruskal-Wallis Test — ard_stats_kruskal_test","text":"Analysis results data Kruskal-Wallis Rank Sum Test. Calculated kruskal.test(data[[variable]], data[[]], ...)","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_kruskal_test.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Kruskal-Wallis Test — ard_stats_kruskal_test","text":"","code":"ard_stats_kruskal_test(data, by, variables)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_kruskal_test.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Kruskal-Wallis Test — ard_stats_kruskal_test","text":"data (data.frame) data frame. (tidy-select) column name compare . variables (tidy-select) column names compared. Independent tests computed variable.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_kruskal_test.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Kruskal-Wallis Test — ard_stats_kruskal_test","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_kruskal_test.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Kruskal-Wallis Test — ard_stats_kruskal_test","text":"","code":"cards::ADSL |>   ard_stats_kruskal_test(by = \"ARM\", variables = \"AGE\") #> {cards} data frame: 4 x 9 #>   group1 variable   context stat_name stat_label      stat #> 1    ARM      AGE stats_kr… statistic  Kruskal-…     1.635 #> 2    ARM      AGE stats_kr…   p.value    p-value     0.442 #> 3    ARM      AGE stats_kr… parameter  Degrees …         2 #> 4    ARM      AGE stats_kr…    method     method Kruskal-… #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_mcnemar_test.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD McNemar's Test — ard_stats_mcnemar_test","title":"ARD McNemar's Test — ard_stats_mcnemar_test","text":"Analysis results data McNemar's statistical test. two functions depending structure data. ard_stats_mcnemar_test() structure expected stats::mcnemar.test() ard_stats_mcnemar_test_long() one row per ID per group","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_mcnemar_test.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD McNemar's Test — ard_stats_mcnemar_test","text":"","code":"ard_stats_mcnemar_test(data, by, variables, ...)  ard_stats_mcnemar_test_long(data, by, variables, id, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_mcnemar_test.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD McNemar's Test — ard_stats_mcnemar_test","text":"data (data.frame) data frame. See details. (tidy-select) column name compare . variables (tidy-select) column names compared. Independent tests computed variable. ... arguments passed stats::mcnemar.test(...) id (tidy-select) column name subject participant ID","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_mcnemar_test.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD McNemar's Test — ard_stats_mcnemar_test","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_mcnemar_test.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"ARD McNemar's Test — ard_stats_mcnemar_test","text":"ard_stats_mcnemar_test() function, data expected one row per subject. data passed stats::mcnemar.test(x = data[[variable]], y = data[[]], ...). Please use table(x = data[[variable]], y = data[[]]) check contingency table.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_mcnemar_test.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD McNemar's Test — ard_stats_mcnemar_test","text":"","code":"cards::ADSL |>   ard_stats_mcnemar_test(by = \"SEX\", variables = \"EFFFL\") #> {cards} data frame: 5 x 9 #>   group1 variable   context stat_name stat_label      stat #> 1    SEX    EFFFL stats_mc… statistic  X-square…    111.91 #> 2    SEX    EFFFL stats_mc…   p.value    p-value         0 #> 3    SEX    EFFFL stats_mc… parameter  Degrees …         1 #> 4    SEX    EFFFL stats_mc…    method     method McNemar'… #> 5    SEX    EFFFL stats_mc…   correct    correct      TRUE #> ℹ 3 more variables: fmt_fn, warning, error  set.seed(1234) cards::ADSL[c(\"USUBJID\", \"TRT01P\")] |>   dplyr::mutate(TYPE = \"PLANNED\") |>   dplyr::rename(TRT01 = TRT01P) %>%   dplyr::bind_rows(dplyr::mutate(., TYPE = \"ACTUAL\", TRT01 = sample(TRT01))) |>   ard_stats_mcnemar_test_long(     by = TYPE,     variable = TRT01,     id = USUBJID   ) #> {cards} data frame: 5 x 9 #>   group1 variable   context stat_name stat_label      stat #> 1   TYPE    TRT01 stats_mc… statistic  X-square…     1.353 #> 2   TYPE    TRT01 stats_mc…   p.value    p-value     0.717 #> 3   TYPE    TRT01 stats_mc… parameter  Degrees …         3 #> 4   TYPE    TRT01 stats_mc…    method     method McNemar'… #> 5   TYPE    TRT01 stats_mc…   correct    correct      TRUE #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_mood_test.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Mood Test — ard_stats_mood_test","title":"ARD Mood Test — ard_stats_mood_test","text":"Analysis results data Mood two sample test scale. Note confused Brown-Mood test medians.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_mood_test.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Mood Test — ard_stats_mood_test","text":"","code":"ard_stats_mood_test(data, by, variables, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_mood_test.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Mood Test — ard_stats_mood_test","text":"data (data.frame) data frame. See details. (tidy-select) column name compare . variables (tidy-select) column name compared. Independent tests run variable. ... arguments passed mood.test(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_mood_test.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Mood Test — ard_stats_mood_test","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_mood_test.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"ARD Mood Test — ard_stats_mood_test","text":"ard_stats_mood_test() function, data expected one row per subject. data passed mood.test(data[[variable]] ~ data[[]], ...).","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_mood_test.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Mood Test — ard_stats_mood_test","text":"","code":"cards::ADSL |>   ard_stats_mood_test(by = \"SEX\", variables = \"AGE\") #> {cards} data frame: 4 x 9 #>   group1 variable   context   stat_name stat_label      stat #> 1    SEX      AGE stats_mo…   statistic  Z-Statis…     0.129 #> 2    SEX      AGE stats_mo…     p.value    p-value     0.897 #> 3    SEX      AGE stats_mo…      method     method Mood two… #> 4    SEX      AGE stats_mo… alternative  Alternat… two.sided #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_oneway_test.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD One-way Test — ard_stats_oneway_test","title":"ARD One-way Test — ard_stats_oneway_test","text":"Analysis results data Testing Equal Means One-Way Layout. calculated oneway.test()","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_oneway_test.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD One-way Test — ard_stats_oneway_test","text":"","code":"ard_stats_oneway_test(formula, data, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_oneway_test.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD One-way Test — ard_stats_oneway_test","text":"formula formula form lhs ~ rhs lhs     gives sample values rhs corresponding groups. data optional matrix data frame (similar: see     model.frame) containing variables     formula formula.  default variables taken     environment(formula). ... additional arguments passed oneway.test(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_oneway_test.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD One-way Test — ard_stats_oneway_test","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_oneway_test.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD One-way Test — ard_stats_oneway_test","text":"","code":"ard_stats_oneway_test(AGE ~ ARM, data = cards::ADSL) #> {cards} data frame: 6 x 7 #>     context stat_name stat_label      stat fmt_fn error #> 1 stats_on…    num.df  Degrees …         2      1       #> 2 stats_on…    den.df  Denomina…   167.237      1       #> 3 stats_on… statistic  F Statis…     0.547      1       #> 4 stats_on…   p.value    p-value      0.58      1       #> 5 stats_on…    method     Method One-way …   NULL       #> 6 stats_on… var.equal  var.equal     FALSE   NULL       #> ℹ 1 more variable: warning"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_prop_test.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD 2-sample proportion test — ard_stats_prop_test","title":"ARD 2-sample proportion test — ard_stats_prop_test","text":"Analysis results data 2-sample test proportions using stats::prop.test().","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_prop_test.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD 2-sample proportion test — ard_stats_prop_test","text":"","code":"ard_stats_prop_test(data, by, variables, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_prop_test.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD 2-sample proportion test — ard_stats_prop_test","text":"data (data.frame) data frame. (tidy-select) column name compare variables (tidy-select) column names compared. Must binary column coded TRUE/FALSE 1/0. Independent tests computed variable. ... arguments passed prop.test(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_prop_test.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD 2-sample proportion test — ard_stats_prop_test","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_prop_test.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD 2-sample proportion test — ard_stats_prop_test","text":"","code":"mtcars |>   ard_stats_prop_test(by = vs, variables = am) #> {cards} data frame: 13 x 9 #>    group1 variable   context   stat_name stat_label      stat #> 1      vs       am stats_pr…    estimate  Rate Dif…    -0.167 #> 2      vs       am stats_pr…   estimate1  Group 1 …     0.333 #> 3      vs       am stats_pr…   estimate2  Group 2 …       0.5 #> 4      vs       am stats_pr…   statistic  X-square…     0.348 #> 5      vs       am stats_pr…     p.value    p-value     0.556 #> 6      vs       am stats_pr…   parameter  Degrees …         1 #> 7      vs       am stats_pr…    conf.low  CI Lower…    -0.571 #> 8      vs       am stats_pr…   conf.high  CI Upper…     0.237 #> 9      vs       am stats_pr…      method     method 2-sample… #> 10     vs       am stats_pr… alternative  alternat… two.sided #> 11     vs       am stats_pr…           p          p           #> 12     vs       am stats_pr…  conf.level  CI Confi…      0.95 #> 13     vs       am stats_pr…     correct  Yates' c…      TRUE #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_t_test.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD t-test — ard_stats_t_test","title":"ARD t-test — ard_stats_t_test","text":"Analysis results data paired non-paired t-tests.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_t_test.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD t-test — ard_stats_t_test","text":"","code":"ard_stats_t_test(data, variables, by = NULL, ...)  ard_stats_paired_t_test(data, by, variables, id, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_t_test.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD t-test — ard_stats_t_test","text":"data (data.frame) data frame. See details. variables (tidy-select) column names compared. Independent t-tests computed variable. (tidy-select) optional column name compare . ... arguments passed t.test(...) id (tidy-select) column name subject participant ID","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_t_test.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD t-test — ard_stats_t_test","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_t_test.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"ARD t-test — ard_stats_t_test","text":"ard_stats_t_test() function, data expected one row per subject. data passed t.test(data[[variable]] ~ data[[]], paired = FALSE, ...). ard_stats_paired_t_test() function, data expected one row per subject per level. t-test calculated, data reshaped wide format one row per subject. data passed t.test(x = data_wide[[<level 1>]], y = data_wide[[<level 2>]], paired = TRUE, ...).","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_t_test.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD t-test — ard_stats_t_test","text":"","code":"cards::ADSL |>   dplyr::filter(ARM %in% c(\"Placebo\", \"Xanomeline High Dose\")) |>   ard_stats_t_test(by = ARM, variables = c(AGE, BMIBL)) #> {cards} data frame: 28 x 9 #>    group1 variable   context   stat_name stat_label      stat #> 1     ARM      AGE stats_t_…    estimate  Mean Dif…     0.828 #> 2     ARM      AGE stats_t_…   estimate1  Group 1 …    75.209 #> 3     ARM      AGE stats_t_…   estimate2  Group 2 …    74.381 #> 4     ARM      AGE stats_t_…   statistic  t Statis…     0.655 #> 5     ARM      AGE stats_t_…     p.value    p-value     0.513 #> 6     ARM      AGE stats_t_…   parameter  Degrees …   167.362 #> 7     ARM      AGE stats_t_…    conf.low  CI Lower…    -1.668 #> 8     ARM      AGE stats_t_…   conf.high  CI Upper…     3.324 #> 9     ARM      AGE stats_t_…      method     method Welch Tw… #> 10    ARM      AGE stats_t_… alternative  alternat… two.sided #> ℹ 18 more rows #> ℹ Use `print(n = ...)` to see more rows #> ℹ 3 more variables: fmt_fn, warning, error  # constructing a paired data set, # where patients receive both treatments cards::ADSL[c(\"ARM\", \"AGE\")] |>   dplyr::filter(ARM %in% c(\"Placebo\", \"Xanomeline High Dose\")) |>   dplyr::mutate(.by = ARM, USUBJID = dplyr::row_number()) |>   dplyr::arrange(USUBJID, ARM) |>   ard_stats_paired_t_test(by = ARM, variables = AGE, id = USUBJID) #> {cards} data frame: 12 x 9 #>    group1 variable   context   stat_name stat_label      stat #> 1     ARM      AGE stats_t_…    estimate  Mean Dif…     0.798 #> 2     ARM      AGE stats_t_…   statistic  t Statis…     0.628 #> 3     ARM      AGE stats_t_…     p.value    p-value     0.531 #> 4     ARM      AGE stats_t_…   parameter  Degrees …        83 #> 5     ARM      AGE stats_t_…    conf.low  CI Lower…    -1.727 #> 6     ARM      AGE stats_t_…   conf.high  CI Upper…     3.322 #> 7     ARM      AGE stats_t_…      method     method Paired t… #> 8     ARM      AGE stats_t_… alternative  alternat… two.sided #> 9     ARM      AGE stats_t_…          mu    H0 Mean         0 #> 10    ARM      AGE stats_t_…      paired  Paired t…      TRUE #> 11    ARM      AGE stats_t_…   var.equal  Equal Va…     FALSE #> 12    ARM      AGE stats_t_…  conf.level  CI Confi…      0.95 #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_wilcox_test.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Wilcoxon Rank-Sum Test — ard_stats_wilcox_test","title":"ARD Wilcoxon Rank-Sum Test — ard_stats_wilcox_test","text":"Analysis results data paired non-paired Wilcoxon Rank-Sum tests.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_wilcox_test.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Wilcoxon Rank-Sum Test — ard_stats_wilcox_test","text":"","code":"ard_stats_wilcox_test(data, variables, by = NULL, ...)  ard_stats_paired_wilcox_test(data, by, variables, id, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_wilcox_test.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Wilcoxon Rank-Sum Test — ard_stats_wilcox_test","text":"data (data.frame) data frame. See details. variables (tidy-select) column names compared. Independent tests computed variable. (tidy-select) optional column name compare . ... arguments passed wilcox.test(...) id (tidy-select) column name subject participant ID.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_wilcox_test.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Wilcoxon Rank-Sum Test — ard_stats_wilcox_test","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_wilcox_test.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"ARD Wilcoxon Rank-Sum Test — ard_stats_wilcox_test","text":"ard_stats_wilcox_test() function, data expected one row per subject. data passed wilcox.test(data[[variable]] ~ data[[]], paired = FALSE, ...). ard_stats_paired_wilcox_test() function, data expected one row per subject per level. test calculated, data reshaped wide format one row per subject. data passed wilcox.test(x = data_wide[[<level 1>]], y = data_wide[[<level 2>]], paired = TRUE, ...).","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_stats_wilcox_test.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Wilcoxon Rank-Sum Test — ard_stats_wilcox_test","text":"","code":"cards::ADSL |>   dplyr::filter(ARM %in% c(\"Placebo\", \"Xanomeline High Dose\")) |>   ard_stats_wilcox_test(by = \"ARM\", variables = \"AGE\") #> {cards} data frame: 12 x 9 #>    group1 variable   context   stat_name stat_label      stat #> 1     ARM      AGE stats_wi…   statistic  X-square…    3862.5 #> 2     ARM      AGE stats_wi…     p.value    p-value     0.435 #> 3     ARM      AGE stats_wi…      method     method Wilcoxon… #> 4     ARM      AGE stats_wi… alternative  alternat… two.sided #> 5     ARM      AGE stats_wi…          mu         mu         0 #> 6     ARM      AGE stats_wi…      paired  Paired t…     FALSE #> 7     ARM      AGE stats_wi…       exact      exact           #> 8     ARM      AGE stats_wi…     correct    correct      TRUE #> 9     ARM      AGE stats_wi…    conf.int   conf.int     FALSE #> 10    ARM      AGE stats_wi…  conf.level  CI Confi…      0.95 #> 11    ARM      AGE stats_wi…    tol.root   tol.root         0 #> 12    ARM      AGE stats_wi… digits.rank  digits.r…       Inf #> ℹ 3 more variables: fmt_fn, warning, error  # constructing a paired data set, # where patients receive both treatments cards::ADSL[c(\"ARM\", \"AGE\")] |>   dplyr::filter(ARM %in% c(\"Placebo\", \"Xanomeline High Dose\")) |>   dplyr::mutate(.by = ARM, USUBJID = dplyr::row_number()) |>   dplyr::arrange(USUBJID, ARM) |>   ard_stats_paired_wilcox_test(by = ARM, variables = AGE, id = USUBJID) #> {cards} data frame: 12 x 9 #>    group1 variable   context   stat_name stat_label      stat #> 1     ARM      AGE stats_wi…   statistic  X-square…      1754 #> 2     ARM      AGE stats_wi…     p.value    p-value     0.522 #> 3     ARM      AGE stats_wi…      method     method Wilcoxon… #> 4     ARM      AGE stats_wi… alternative  alternat… two.sided #> 5     ARM      AGE stats_wi…          mu         mu         0 #> 6     ARM      AGE stats_wi…      paired  Paired t…      TRUE #> 7     ARM      AGE stats_wi…       exact      exact           #> 8     ARM      AGE stats_wi…     correct    correct      TRUE #> 9     ARM      AGE stats_wi…    conf.int   conf.int     FALSE #> 10    ARM      AGE stats_wi…  conf.level  CI Confi…      0.95 #> 11    ARM      AGE stats_wi…    tol.root   tol.root         0 #> 12    ARM      AGE stats_wi… digits.rank  digits.r…       Inf #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survey_svychisq.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Survey Chi-Square Test — ard_survey_svychisq","title":"ARD Survey Chi-Square Test — ard_survey_svychisq","text":"Analysis results data survey Chi-Square test using survey::svychisq(). two-way comparisons supported.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survey_svychisq.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Survey Chi-Square Test — ard_survey_svychisq","text":"","code":"ard_survey_svychisq(data, by, variables, statistic = \"F\", ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survey_svychisq.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Survey Chi-Square Test — ard_survey_svychisq","text":"data (survey.design) survey design object often created survey package (tidy-select) column name compare . variables (tidy-select) column names compared. Independent tests computed variable. statistic (character) statistic used estimate Chisq p-value. Default Rao-Scott second-order correction (\"F\"). See survey::svychisq available statistics options. ... arguments passed survey::svychisq().","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survey_svychisq.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Survey Chi-Square Test — ard_survey_svychisq","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survey_svychisq.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Survey Chi-Square Test — ard_survey_svychisq","text":"","code":"data(api, package = \"survey\") dclus1 <- survey::svydesign(id = ~dnum, weights = ~pw, data = apiclus1, fpc = ~fpc)  ard_survey_svychisq(dclus1, variables = sch.wide, by = comp.imp, statistic = \"F\") #> {cards} data frame: 5 x 9 #>     group1 variable   context stat_name stat_label      stat #> 1 comp.imp sch.wide survey_s…       ndf  Nominato…         1 #> 2 comp.imp sch.wide survey_s…       ddf  Denomina…        14 #> 3 comp.imp sch.wide survey_s… statistic  Statistic   236.895 #> 4 comp.imp sch.wide survey_s…   p.value    p-value         0 #> 5 comp.imp sch.wide survey_s…    method     method Pearson'… #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survey_svycontinuous.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Continuous Survey Statistics — ard_survey_svycontinuous","title":"ARD Continuous Survey Statistics — ard_survey_svycontinuous","text":"Returns ARD weighted statistics using {survey} package.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survey_svycontinuous.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Continuous Survey Statistics — ard_survey_svycontinuous","text":"","code":"ard_survey_svycontinuous(   data,   variables,   by = NULL,   statistic = everything() ~ c(\"median\", \"p25\", \"p75\"),   fmt_fn = NULL,   stat_label = NULL )"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survey_svycontinuous.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Continuous Survey Statistics — ard_survey_svycontinuous","text":"data (survey.design) design object often created survey::svydesign(). variables (tidy-select) columns include summaries. Default everything(). (tidy-select) results calculated combinations columns specified, including unobserved combinations unobserved factor levels. statistic (formula-list-selector) named list, list formulas, single formula list element character vector statistic names include. See options. fmt_fn (formula-list-selector) named list, list formulas, single formula list element named list functions (RHS formula), e.g. list(mpg = list(mean = \\(x) round(x, digits = 2) |> .character)). stat_label (formula-list-selector) named list, list formulas, single formula list element either named list list formulas defining statistic labels, e.g. everything() ~ list(mean = \"Mean\", sd = \"SD\") everything() ~ list(mean ~ \"Mean\", sd ~ \"SD\").","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survey_svycontinuous.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Continuous Survey Statistics — ard_survey_svycontinuous","text":"ARD data frame class 'card'","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survey_svycontinuous.html","id":"statistic-argument","dir":"Reference","previous_headings":"","what":"statistic argument","title":"ARD Continuous Survey Statistics — ard_survey_svycontinuous","text":"following statistics available: 'mean', 'median', 'min', 'max', 'sum', 'var', 'sd', 'mean.std.error', 'deff', 'p##', 'p##' percentiles ## integer 0 100.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survey_svycontinuous.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Continuous Survey Statistics — ard_survey_svycontinuous","text":"","code":"data(api, package = \"survey\") dclus1 <- survey::svydesign(id = ~dnum, weights = ~pw, data = apiclus1, fpc = ~fpc)  ard_survey_svycontinuous(   data = dclus1,   variables = api00,   by = stype ) #> {cards} data frame: 9 x 10 #>   group1 group1_level variable stat_name stat_label stat #> 1  stype            E    api00    median     Median  652 #> 2  stype            H    api00    median     Median  608 #> 3  stype            M    api00    median     Median  642 #> 4  stype            E    api00       p25  25% Perc…  553 #> 5  stype            H    api00       p25  25% Perc…  529 #> 6  stype            M    api00       p25  25% Perc…  547 #> 7  stype            E    api00       p75  75% Perc…  729 #> 8  stype            H    api00       p75  75% Perc…  703 #> 9  stype            M    api00       p75  75% Perc…  699 #> ℹ 4 more variables: context, fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survey_svyranktest.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Survey rank test — ard_survey_svyranktest","title":"ARD Survey rank test — ard_survey_svyranktest","text":"Analysis results data survey wilcox test using survey::svyranktest().","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survey_svyranktest.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Survey rank test — ard_survey_svyranktest","text":"","code":"ard_survey_svyranktest(data, by, variables, test, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survey_svyranktest.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Survey rank test — ard_survey_svyranktest","text":"data (survey.design) survey design object often created survey::svydesign() (tidy-select) column name compare variables (tidy-select) column names compared. Independent tests run variable. test (string) string denote rank test use: \"wilcoxon\", \"vanderWaerden\", \"median\", \"KruskalWallis\" ... arguments passed survey::svyranktest()","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survey_svyranktest.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Survey rank test — ard_survey_svyranktest","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survey_svyranktest.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Survey rank test — ard_survey_svyranktest","text":"","code":"data(api, package = \"survey\") dclus2 <- survey::svydesign(id = ~ dnum + snum, fpc = ~ fpc1 + fpc2, data = apiclus2)  ard_survey_svyranktest(dclus2, variables = enroll, by = comp.imp, test = \"wilcoxon\") #> {cards} data frame: 6 x 9 #>     group1 variable   context   stat_name stat_label      stat #> 1 comp.imp   enroll survey_s…    estimate  Median o…    -0.106 #> 2 comp.imp   enroll survey_s…   statistic  Statistic    -1.719 #> 3 comp.imp   enroll survey_s…     p.value    p-value     0.094 #> 4 comp.imp   enroll survey_s…   parameter  Degrees …        36 #> 5 comp.imp   enroll survey_s…      method     method Design-b… #> 6 comp.imp   enroll survey_s… alternative  Alternat… two.sided #> ℹ 3 more variables: fmt_fn, warning, error ard_survey_svyranktest(dclus2, variables = enroll, by = comp.imp, test = \"vanderWaerden\") #> {cards} data frame: 6 x 9 #>     group1 variable   context   stat_name stat_label      stat #> 1 comp.imp   enroll survey_s…    estimate  Median o…    -0.379 #> 2 comp.imp   enroll survey_s…   statistic  Statistic    -1.584 #> 3 comp.imp   enroll survey_s…     p.value    p-value     0.122 #> 4 comp.imp   enroll survey_s…   parameter  Degrees …        36 #> 5 comp.imp   enroll survey_s…      method     method Design-b… #> 6 comp.imp   enroll survey_s… alternative  Alternat… two.sided #> ℹ 3 more variables: fmt_fn, warning, error ard_survey_svyranktest(dclus2, variables = enroll, by = comp.imp, test = \"median\") #> {cards} data frame: 6 x 9 #>     group1 variable   context   stat_name stat_label      stat #> 1 comp.imp   enroll survey_s…    estimate  Median o…    -0.124 #> 2 comp.imp   enroll survey_s…   statistic  Statistic    -0.914 #> 3 comp.imp   enroll survey_s…     p.value    p-value     0.367 #> 4 comp.imp   enroll survey_s…   parameter  Degrees …        36 #> 5 comp.imp   enroll survey_s…      method     method Design-b… #> 6 comp.imp   enroll survey_s… alternative  Alternat… two.sided #> ℹ 3 more variables: fmt_fn, warning, error ard_survey_svyranktest(dclus2, variables = enroll, by = comp.imp, test = \"KruskalWallis\") #> {cards} data frame: 6 x 9 #>     group1 variable   context   stat_name stat_label      stat #> 1 comp.imp   enroll survey_s…    estimate  Median o…    -0.106 #> 2 comp.imp   enroll survey_s…   statistic  Statistic    -1.719 #> 3 comp.imp   enroll survey_s…     p.value    p-value     0.094 #> 4 comp.imp   enroll survey_s…   parameter  Degrees …        36 #> 5 comp.imp   enroll survey_s…      method     method Design-b… #> 6 comp.imp   enroll survey_s… alternative  Alternat… two.sided #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survey_svyttest.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Survey t-test — ard_survey_svyttest","title":"ARD Survey t-test — ard_survey_svyttest","text":"Analysis results data survey t-test using survey::svyttest().","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survey_svyttest.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Survey t-test — ard_survey_svyttest","text":"","code":"ard_survey_svyttest(data, by, variables, conf.level = 0.95, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survey_svyttest.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Survey t-test — ard_survey_svyttest","text":"data (survey.design) survey design object often created survey::svydesign() (tidy-select) column name compare variables (tidy-select) column names compared. Independent tests run variable. conf.level (double) confidence level returned confidence interval. Must c(0, 1). Default 0.95 ... arguments passed survey::svyttest()","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survey_svyttest.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Survey t-test — ard_survey_svyttest","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survey_svyttest.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Survey t-test — ard_survey_svyttest","text":"","code":"data(api, package = \"survey\") dclus2 <- survey::svydesign(id = ~ dnum + snum, fpc = ~ fpc1 + fpc2, data = apiclus2)  ard_survey_svyttest(dclus2, variables = enroll, by = comp.imp, conf.level = 0.9) #> {cards} data frame: 9 x 9 #>     group1 variable   context   stat_name stat_label      stat #> 1 comp.imp   enroll survey_s…    estimate       Mean  -225.737 #> 2 comp.imp   enroll survey_s…   statistic  t Statis…    -2.888 #> 3 comp.imp   enroll survey_s…     p.value    p-value     0.007 #> 4 comp.imp   enroll survey_s…   parameter  Degrees …        36 #> 5 comp.imp   enroll survey_s…      method     method Design-b… #> 6 comp.imp   enroll survey_s… alternative  alternat… two.sided #> 7 comp.imp   enroll survey_s…    conf.low  CI Lower…   -357.69 #> 8 comp.imp   enroll survey_s…   conf.high  CI Upper…   -93.784 #> 9 comp.imp   enroll survey_s…  conf.level  CI Confi…       0.9 #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survival_survdiff.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD for Difference in Survival — ard_survival_survdiff","title":"ARD for Difference in Survival — ard_survival_survdiff","text":"Analysis results data comparison survival using survival::survdiff().","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survival_survdiff.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD for Difference in Survival — ard_survival_survdiff","text":"","code":"ard_survival_survdiff(formula, data, rho = 0, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survival_survdiff.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD for Difference in Survival — ard_survival_survdiff","text":"formula (formula) formula data (data.frame) data frame rho (scalar numeric) numeric scalar passed survival::survdiff(rho). Default rho=0. ... additional arguments passed survival::survdiff()","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survival_survdiff.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD for Difference in Survival — ard_survival_survdiff","text":"ARD data frame class 'card'","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survival_survdiff.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD for Difference in Survival — ard_survival_survdiff","text":"","code":"library(survival) library(ggsurvfit) #> Loading required package: ggplot2  ard_survival_survdiff(Surv_CNSR(AVAL, CNSR) ~ TRTA, data = cards::ADTTE) #> {cards} data frame: 4 x 8 #>   variable   context stat_name stat_label      stat fmt_fn #> 1     TRTA survival… statistic  X^2 Stat…     60.27      1 #> 2     TRTA survival…        df  Degrees …         2      1 #> 3     TRTA survival…   p.value    p-value         0      1 #> 4     TRTA survival…    method     method Log-rank…   NULL #> ℹ 2 more variables: warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survival_survfit.html","id":null,"dir":"Reference","previous_headings":"","what":"ARD Survival Estimates — ard_survival_survfit","title":"ARD Survival Estimates — ard_survival_survfit","text":"Analysis results data survival quantiles x-year survival estimates, extracted survival::survfit() model.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survival_survfit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ARD Survival Estimates — ard_survival_survfit","text":"","code":"ard_survival_survfit(x, times = NULL, probs = NULL, type = NULL)"},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survival_survfit.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ARD Survival Estimates — ard_survival_survfit","text":"x (survival::survfit()) survival::survfit() object. See details. times (numeric) vector times return survival probabilities. probs (numeric) vector probabilities values (0,1) specifying survival quantiles return. type (string NULL) type statistic report. Available Kaplan-Meier time estimates , otherwise type ignored. Default NULL. Must one following:","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survival_survfit.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ARD Survival Estimates — ard_survival_survfit","text":"ARD data frame class 'card'","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survival_survfit.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"ARD Survival Estimates — ard_survival_survfit","text":"one either times probs parameters can specified. Times provided using scale time variable used fit provided survival fit model.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/ard_survival_survfit.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"ARD Survival Estimates — ard_survival_survfit","text":"","code":"library(survival) library(ggsurvfit)  survfit(Surv_CNSR(AVAL, CNSR) ~ TRTA, cards::ADTTE) |>   ard_survival_survfit(times = c(60, 180)) #> {cards} data frame: 18 x 11 #>    group1 group1_level variable variable_level stat_name stat_label  stat #> 1    TRTA      Placebo     time             60  estimate  Survival… 0.768 #> 2    TRTA      Placebo     time             60 conf.high  CI Upper… 0.866 #> 3    TRTA      Placebo     time             60  conf.low  CI Lower… 0.682 #> 4    TRTA      Placebo     time            180  estimate  Survival… 0.626 #> 5    TRTA      Placebo     time            180 conf.high  CI Upper… 0.746 #> 6    TRTA      Placebo     time            180  conf.low  CI Lower… 0.526 #> 7    TRTA    Xanomeli…     time             60  estimate  Survival… 0.243 #> 8    TRTA    Xanomeli…     time             60 conf.high  CI Upper… 0.373 #> 9    TRTA    Xanomeli…     time             60  conf.low  CI Lower… 0.158 #> 10   TRTA    Xanomeli…     time            180  estimate  Survival… 0.092 #> 11   TRTA    Xanomeli…     time            180 conf.high  CI Upper… 0.221 #> 12   TRTA    Xanomeli…     time            180  conf.low  CI Lower… 0.038 #> 13   TRTA    Xanomeli…     time             60  estimate  Survival… 0.311 #> 14   TRTA    Xanomeli…     time             60 conf.high  CI Upper… 0.441 #> 15   TRTA    Xanomeli…     time             60  conf.low  CI Lower… 0.219 #> 16   TRTA    Xanomeli…     time            180  estimate  Survival… 0.126 #> 17   TRTA    Xanomeli…     time            180 conf.high  CI Upper… 0.249 #> 18   TRTA    Xanomeli…     time            180  conf.low  CI Lower… 0.064 #> ℹ 4 more variables: context, fmt_fn, warning, error  survfit(Surv_CNSR(AVAL, CNSR) ~ TRTA, cards::ADTTE) |>   ard_survival_survfit(probs = c(0.25, 0.5, 0.75)) #> {cards} data frame: 27 x 11 #>    group1 group1_level variable variable_level stat_name stat_label stat #> 1    TRTA      Placebo     prob           0.25  estimate  Survival…   70 #> 2    TRTA      Placebo     prob           0.25 conf.high  CI Upper…  177 #> 3    TRTA      Placebo     prob           0.25  conf.low  CI Lower…   35 #> 4    TRTA      Placebo     prob            0.5  estimate  Survival…   NA #> 5    TRTA      Placebo     prob            0.5 conf.high  CI Upper…   NA #> 6    TRTA      Placebo     prob            0.5  conf.low  CI Lower…   NA #> 7    TRTA      Placebo     prob           0.75  estimate  Survival…   NA #> 8    TRTA      Placebo     prob           0.75 conf.high  CI Upper…   NA #> 9    TRTA      Placebo     prob           0.75  conf.low  CI Lower…   NA #> 10   TRTA    Xanomeli…     prob           0.25  estimate  Survival…   14 #> ℹ 17 more rows #> ℹ Use `print(n = ...)` to see more rows #> ℹ 4 more variables: context, fmt_fn, warning, error  # Competing Risks Example --------------------------- set.seed(1) ADTTE_MS <- cards::ADTTE %>%   dplyr::mutate(     CNSR = dplyr::case_when(       CNSR == 0 ~ \"censor\",       runif(dplyr::n()) < 0.5 ~ \"death from cancer\",       TRUE ~ \"death other causes\"     ) %>% factor()   )  survfit(Surv(AVAL, CNSR) ~ TRTA, data = ADTTE_MS) %>%   ard_survival_survfit(times = c(60, 180)) #> Multi-state model detected. Showing probabilities into state 'death from #> cancer'. #> {cards} data frame: 18 x 11 #>    group1 group1_level variable variable_level stat_name stat_label  stat #> 1    TRTA      Placebo     time             60  estimate  Survival… 0.054 #> 2    TRTA      Placebo     time             60 conf.high  CI Upper…  0.14 #> 3    TRTA      Placebo     time             60  conf.low  CI Lower… 0.021 #> 4    TRTA      Placebo     time            180  estimate  Survival… 0.226 #> 5    TRTA      Placebo     time            180 conf.high  CI Upper… 0.361 #> 6    TRTA      Placebo     time            180  conf.low  CI Lower… 0.142 #> 7    TRTA    Xanomeli…     time             60  estimate  Survival… 0.137 #> 8    TRTA    Xanomeli…     time             60 conf.high  CI Upper… 0.311 #> 9    TRTA    Xanomeli…     time             60  conf.low  CI Lower…  0.06 #> 10   TRTA    Xanomeli…     time            180  estimate  Survival…  0.51 #> 11   TRTA    Xanomeli…     time            180 conf.high  CI Upper… 0.892 #> 12   TRTA    Xanomeli…     time            180  conf.low  CI Lower… 0.292 #> 13   TRTA    Xanomeli…     time             60  estimate  Survival… 0.162 #> 14   TRTA    Xanomeli…     time             60 conf.high  CI Upper…  0.33 #> 15   TRTA    Xanomeli…     time             60  conf.low  CI Lower…  0.08 #> 16   TRTA    Xanomeli…     time            180  estimate  Survival… 0.244 #> 17   TRTA    Xanomeli…     time            180 conf.high  CI Upper… 0.516 #> 18   TRTA    Xanomeli…     time            180  conf.low  CI Lower… 0.115 #> ℹ 4 more variables: context, fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/cardx-package.html","id":null,"dir":"Reference","previous_headings":"","what":"cardx: Extra Analysis Results Data Utilities — cardx-package","title":"cardx: Extra Analysis Results Data Utilities — cardx-package","text":"Create extra Analysis Results Data (ARD) summary objects. package supplements simple ARD functions 'cards' package, exporting functions put statistical results ARD format. objects used re-used construct summary tables, visualizations, written reports.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/cardx/reference/cardx-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"cardx: Extra Analysis Results Data Utilities — cardx-package","text":"Maintainer: Daniel Sjoberg danield.sjoberg@gmail.com Authors: Abinaya Yogasekaram abinaya.yogasekaram@contractors.roche.com Emily de la Rua emily.de_la_rua@contractors.roche.com contributors: F. Hoffmann-La Roche AG [copyright holder, funder]","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/construction_helpers.html","id":null,"dir":"Reference","previous_headings":"","what":"Construction Helpers — construction_helpers","title":"Construction Helpers — construction_helpers","text":"functions help construct calls various types models.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/construction_helpers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Construction Helpers — construction_helpers","text":"","code":"construct_model(x, ...)  # S3 method for data.frame construct_model(   x,   formula,   method,   method.args = list(),   package = \"base\",   env = caller_env(),   ... )  # S3 method for survey.design construct_model(   x,   formula,   method,   method.args = list(),   package = \"survey\",   env = caller_env(),   ... )  reformulate2(   termlabels,   response = NULL,   intercept = TRUE,   pattern_term = \"[ \\n\\r]\",   pattern_response = \"[ \\n\\r]\",   env = parent.frame() )  bt(x, pattern = \"[ \\n\\r]\")  bt_strip(x)"},{"path":"https://insightsengineering.github.io/cardx/reference/construction_helpers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Construction Helpers — construction_helpers","text":"x construct_model.data.frame() (data.frame) data frame construct_model.survey.design() (survey.design) survey design object bt()/bt_strip() (character) character vector, typically variable names ... dots future extensions must empty. formula (formula) formula method (string) string naming function called, e.g. \"glm\". function belongs library attached, package name must specified package argument. method.args (named list) named list arguments passed fn. package (string) string package name temporarily loaded function specified method executed. env environment evaluate expr. environment applicable quosures environments. termlabels character vector giving right-hand side     model formula.  zero-length. response character string, symbol call giving left-hand     side model formula, NULL. intercept logical: formula intercept? pattern_term, pattern_response passed bt(pattern) arguments stats::reformulate(termlabels, response). pattern (string) regular expression string. regex matches, backticks added string. NULL, backticks added.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/construction_helpers.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Construction Helpers — construction_helpers","text":"depends calling function","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/construction_helpers.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Construction Helpers — construction_helpers","text":"construct_model(): Builds models form method(data = data, formula = formula, method.args!!!). package argument specified, package temporarily attached model evaluated. reformulate2(): copy reformulate() except variable names contain space wrapped backticks. bt(): Adds backticks character vector. bt_strip(): Removes backticks string begins ends backtick.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/construction_helpers.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Construction Helpers — construction_helpers","text":"","code":"construct_model(   x = mtcars,   formula = am ~ mpg + (1 | vs),   method = \"glmer\",   method.args = list(family = binomial),   package = \"lme4\" ) #> Generalized linear mixed model fit by maximum likelihood (Laplace #>   Approximation) [glmerMod] #>  Family: binomial  ( logit ) #> Formula: am ~ mpg + (1 | vs) #>    Data: structure(list(mpg = c(21, 21, 22.8, 21.4, 18.7, 18.1, 14.3,   #> 24.4, 22.8, 19.2, 17.8, 16.4, 17.3, 15.2, 10.4, 10.4, 14.7, 32.4,   #> 30.4, 33.9, 21.5, 15.5, 15.2, 13.3, 19.2, 27.3, 26, 30.4, 15.8,   #> 19.7, 15, 21.4), cyl = c(6, 6, 4, 6, 8, 6, 8, 4, 4, 6, 6, 8,   #> 8, 8, 8, 8, 8, 4, 4, 4, 4, 8, 8, 8, 8, 4, 4, 4, 8, 6, 8, 4),   #>     disp = c(160, 160, 108, 258, 360, 225, 360, 146.7, 140.8,   #>     167.6, 167.6, 275.8, 275.8, 275.8, 472, 460, 440, 78.7, 75.7,   #>     71.1, 120.1, 318, 304, 350, 400, 79, 120.3, 95.1, 351, 145,   #>     301, 121), hp = c(110, 110, 93, 110, 175, 105, 245, 62, 95,   #>     123, 123, 180, 180, 180, 205, 215, 230, 66, 52, 65, 97, 150,   #>     150, 245, 175, 66, 91, 113, 264, 175, 335, 109), drat = c(3.9,   #>     3.9, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 3.92, 3.92, 3.92,   #>     3.07, 3.07, 3.07, 2.93, 3, 3.23, 4.08, 4.93, 4.22, 3.7, 2.76,   #>     3.15, 3.73, 3.08, 4.08, 4.43, 3.77, 4.22, 3.62, 3.54, 4.11  #>     ), wt = c(2.62, 2.875, 2.32, 3.215, 3.44, 3.46, 3.57, 3.19,   #>     3.15, 3.44, 3.44, 4.07, 3.73, 3.78, 5.25, 5.424, 5.345, 2.2,   #>     1.615, 1.835, 2.465, 3.52, 3.435, 3.84, 3.845, 1.935, 2.14,   #>     1.513, 3.17, 2.77, 3.57, 2.78), qsec = c(16.46, 17.02, 18.61,   #>     19.44, 17.02, 20.22, 15.84, 20, 22.9, 18.3, 18.9, 17.4, 17.6,   #>     18, 17.98, 17.82, 17.42, 19.47, 18.52, 19.9, 20.01, 16.87,   #>     17.3, 15.41, 17.05, 18.9, 16.7, 16.9, 14.5, 15.5, 14.6, 18.6  #>     ), vs = c(0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0,   #>     0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1), am = c(1,   #>     1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1,   #>     0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1), gear = c(4, 4, 4, 3,   #>     3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 3, 3,   #>     3, 3, 4, 5, 5, 5, 5, 5, 4), carb = c(4, 4, 1, 1, 2, 1, 4,   #>     2, 2, 4, 4, 3, 3, 3, 4, 4, 4, 1, 2, 1, 1, 2, 2, 4, 2, 1,   #>     2, 2, 4, 6, 8, 2)), row.names = c(\"Mazda RX4\", \"Mazda RX4 Wag\",   #> \"Datsun 710\", \"Hornet 4 Drive\", \"Hornet Sportabout\", \"Valiant\",   #> \"Duster 360\", \"Merc 240D\", \"Merc 230\", \"Merc 280\", \"Merc 280C\",   #> \"Merc 450SE\", \"Merc 450SL\", \"Merc 450SLC\", \"Cadillac Fleetwood\",   #> \"Lincoln Continental\", \"Chrysler Imperial\", \"Fiat 128\", \"Honda Civic\",   #> \"Toyota Corolla\", \"Toyota Corona\", \"Dodge Challenger\", \"AMC Javelin\",   #> \"Camaro Z28\", \"Pontiac Firebird\", \"Fiat X1-9\", \"Porsche 914-2\",   #> \"Lotus Europa\", \"Ford Pantera L\", \"Ferrari Dino\", \"Maserati Bora\",   #> \"Volvo 142E\"), class = \"data.frame\") #>      AIC      BIC   logLik deviance df.resid  #>  35.2503  39.6475 -14.6251  29.2503       29  #> Random effects: #>  Groups Name        Std.Dev. #>  vs     (Intercept) 0.7896   #> Number of obs: 32, groups:  vs, 2 #> Fixed Effects: #> (Intercept)          mpg   #>     -8.7018       0.4085    construct_model(   x = mtcars |> dplyr::rename(`M P G` = mpg),   formula = reformulate2(c(\"M P G\", \"cyl\"), response = \"hp\"),   method = \"lm\" ) |>   ard_regression() |>   dplyr::filter(stat_name %in% c(\"term\", \"estimate\", \"p.value\")) #> {cards} data frame: 6 x 6 #>   variable   context stat_name stat_label    stat fmt_fn #> 1    M P G regressi…      term       term `M P G`   NULL #> 2    M P G regressi…  estimate  Coeffici…  -2.775      1 #> 3    M P G regressi…   p.value    p-value   0.213      1 #> 4      cyl regressi…      term       term     cyl   NULL #> 5      cyl regressi…  estimate  Coeffici…  23.979      1 #> 6      cyl regressi…   p.value    p-value   0.003      1"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-extract_wald_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract data from wald.test object — .extract_wald_results","title":"Extract data from wald.test object — .extract_wald_results","text":"Extract data wald.test object","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-extract_wald_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract data from wald.test object — .extract_wald_results","text":"","code":".extract_wald_results(wald_test)"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-extract_wald_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract data from wald.test object — .extract_wald_results","text":"wald_test (data.frame) wald test object object aod::wald.test()","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-extract_wald_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract data from wald.test object — .extract_wald_results","text":"data frame containing wald test results.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_cohens_d_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert Cohen's D Test to ARD — .format_cohens_d_results","title":"Convert Cohen's D Test to ARD — .format_cohens_d_results","text":"Convert Cohen's D Test ARD","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_cohens_d_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert Cohen's D Test to ARD — .format_cohens_d_results","text":"","code":".format_cohens_d_results(by, variable, lst_tidy, paired, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_cohens_d_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert Cohen's D Test to ARD — .format_cohens_d_results","text":"(string) column name variable (string) variable column name lst_tidy (named list) list tidied results constructed eval_capture_conditions(), e.g. eval_capture_conditions(t.test(mtcars$mpg ~ mtcars$) |> broom::tidy()). paired TRUE, values x y considered paired. produces effect size equivalent one-sample effect size x - y. See also repeated_measures_d() options. ... passed cohens_d(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_cohens_d_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert Cohen's D Test to ARD — .format_cohens_d_results","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_cohens_d_results.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert Cohen's D Test to ARD — .format_cohens_d_results","text":"","code":"cardx:::.format_cohens_d_results(   by = \"ARM\",   variable = \"AGE\",   paired = FALSE,   lst_tidy =     cards::eval_capture_conditions(       effectsize::hedges_g(data[[variable]] ~ data[[by]], paired = FALSE) |>         parameters::standardize_names(style = \"broom\")     ) ) #> {cards} data frame: 8 x 9 #>   group1 variable   stat_name stat_label      stat     error #> 1    ARM      AGE    estimate  Effect S…           could no… #> 2    ARM      AGE  conf.level  CI Confi…           could no… #> 3    ARM      AGE    conf.low  CI Lower…           could no… #> 4    ARM      AGE   conf.high  CI Upper…           could no… #> 5    ARM      AGE          mu    H0 Mean         0 could no… #> 6    ARM      AGE      paired  Paired t…     FALSE could no… #> 7    ARM      AGE   pooled_sd  Pooled S…      TRUE could no… #> 8    ARM      AGE alternative  Alternat… two.sided could no… #> ℹ 3 more variables: context, fmt_fn, warning"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_hedges_g_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert Hedge's G Test to ARD — .format_hedges_g_results","title":"Convert Hedge's G Test to ARD — .format_hedges_g_results","text":"Convert Hedge's G Test ARD","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_hedges_g_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert Hedge's G Test to ARD — .format_hedges_g_results","text":"","code":".format_hedges_g_results(by, variable, lst_tidy, paired, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_hedges_g_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert Hedge's G Test to ARD — .format_hedges_g_results","text":"(string) column name variable (string) variable column name lst_tidy (named list) list tidied results constructed eval_capture_conditions(), e.g. eval_capture_conditions(t.test(mtcars$mpg ~ mtcars$) |> broom::tidy()). paired TRUE, values x y considered paired. produces effect size equivalent one-sample effect size x - y. See also repeated_measures_d() options. ... passed hedges_g(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_hedges_g_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert Hedge's G Test to ARD — .format_hedges_g_results","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_hedges_g_results.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert Hedge's G Test to ARD — .format_hedges_g_results","text":"","code":"cardx:::.format_hedges_g_results(   by = \"ARM\",   variable = \"AGE\",   paired = FALSE,   lst_tidy =     cards::eval_capture_conditions(       effectsize::hedges_g(data[[variable]] ~ data[[by]], paired = FALSE) |>         parameters::standardize_names(style = \"broom\")     ) ) #> {cards} data frame: 8 x 9 #>   group1 variable   stat_name stat_label      stat     error #> 1    ARM      AGE    estimate  Effect S…           could no… #> 2    ARM      AGE  conf.level  CI Confi…           could no… #> 3    ARM      AGE    conf.low  CI Lower…           could no… #> 4    ARM      AGE   conf.high  CI Upper…           could no… #> 5    ARM      AGE          mu    H0 Mean         0 could no… #> 6    ARM      AGE      paired  Paired t…     FALSE could no… #> 7    ARM      AGE   pooled_sd  Pooled S…      TRUE could no… #> 8    ARM      AGE alternative  Alternat… two.sided could no… #> ℹ 3 more variables: context, fmt_fn, warning"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_mcnemartest_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert McNemar's test to ARD — .format_mcnemartest_results","title":"Convert McNemar's test to ARD — .format_mcnemartest_results","text":"Convert McNemar's test ARD","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_mcnemartest_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert McNemar's test to ARD — .format_mcnemartest_results","text":"","code":".format_mcnemartest_results(by, variable, lst_tidy, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_mcnemartest_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert McNemar's test to ARD — .format_mcnemartest_results","text":"(string) column name variable (string) variable column name lst_tidy (named list) list tidied results constructed eval_capture_conditions(), e.g. eval_capture_conditions(t.test(mtcars$mpg ~ mtcars$) |> broom::tidy()). ... passed stats::mcnemar.test(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_mcnemartest_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert McNemar's test to ARD — .format_mcnemartest_results","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_mcnemartest_results.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert McNemar's test to ARD — .format_mcnemartest_results","text":"","code":"cardx:::.format_mcnemartest_results(   by = \"ARM\",   variable = \"AGE\",   lst_tidy =     cards::eval_capture_conditions(       stats::mcnemar.test(cards::ADSL[[\"SEX\"]], cards::ADSL[[\"EFFFL\"]]) |>         broom::tidy()     ) ) #> {cards} data frame: 5 x 9 #>   group1 variable   context stat_name stat_label      stat #> 1    ARM      AGE stats_mc… statistic  X-square…    111.91 #> 2    ARM      AGE stats_mc…   p.value    p-value         0 #> 3    ARM      AGE stats_mc… parameter  Degrees …         1 #> 4    ARM      AGE stats_mc…    method     method McNemar'… #> 5    ARM      AGE stats_mc…   correct    correct      TRUE #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_moodtest_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert mood test results to ARD — .format_moodtest_results","title":"Convert mood test results to ARD — .format_moodtest_results","text":"Convert mood test results ARD","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_moodtest_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert mood test results to ARD — .format_moodtest_results","text":"","code":".format_moodtest_results(by, variable, lst_tidy, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_moodtest_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert mood test results to ARD — .format_moodtest_results","text":"(string) column name variable (string) variable column name lst_tidy (named list) list tidied results constructed eval_capture_conditions(), e.g. eval_capture_conditions(t.test(mtcars$mpg ~ mtcars$) |> broom::tidy()). ... passed mood.test(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_moodtest_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert mood test results to ARD — .format_moodtest_results","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_moodtest_results.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert mood test results to ARD — .format_moodtest_results","text":"","code":"cardx:::.format_moodtest_results(   by = \"SEX\",   variable = \"AGE\",   lst_tidy =     cards::eval_capture_conditions(       stats::mood.test(ADSL[[\"AGE\"]] ~ ADSL[[\"SEX\"]]) |>         broom::tidy()     ) ) #> {cards} data frame: 4 x 9 #>   group1 variable   stat_name stat_label stat     error #> 1    SEX      AGE   statistic  Z-Statis…      object '… #> 2    SEX      AGE     p.value    p-value      object '… #> 3    SEX      AGE      method     method      object '… #> 4    SEX      AGE alternative  Alternat…      object '… #> ℹ 3 more variables: context, fmt_fn, warning"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_proptest_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert prop.test to ARD — .format_proptest_results","title":"Convert prop.test to ARD — .format_proptest_results","text":"Convert prop.test ARD","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_proptest_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert prop.test to ARD — .format_proptest_results","text":"","code":".format_proptest_results(by, variable, lst_tidy, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_proptest_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert prop.test to ARD — .format_proptest_results","text":"(string) column name variable (string) variable column name lst_tidy (named list) list tidied results constructed eval_capture_conditions(), e.g. eval_capture_conditions(t.test(mtcars$mpg ~ mtcars$) |> broom::tidy()). ... passed prop.test(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_proptest_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert prop.test to ARD — .format_proptest_results","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_survfit_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert Tidied Survival Fit to ARD — .format_survfit_results","title":"Convert Tidied Survival Fit to ARD — .format_survfit_results","text":"Convert Tidied Survival Fit ARD","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_survfit_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert Tidied Survival Fit to ARD — .format_survfit_results","text":"","code":".format_survfit_results(tidy_survfit)"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_survfit_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert Tidied Survival Fit to ARD — .format_survfit_results","text":"ARD data frame class 'card'","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_survfit_results.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert Tidied Survival Fit to ARD — .format_survfit_results","text":"","code":"cardx:::.format_survfit_results(   broom::tidy(survival::survfit(survival::Surv(AVAL, CNSR) ~ TRTA, cards::ADTTE)) ) #> {cards} data frame: 483 x 14 #>    group1 group1_level variable variable_level stat_name stat_label stat n.risk #> 1    TRTA      Placebo     time              1  estimate  Survival…    1     86 #> 2    TRTA      Placebo     time              1 conf.high  CI Upper…    1     86 #> 3    TRTA      Placebo     time              1  conf.low  CI Lower…    1     86 #> 4    TRTA      Placebo     time              2  estimate  Survival…    1     85 #> 5    TRTA      Placebo     time              2 conf.high  CI Upper…    1     85 #> 6    TRTA      Placebo     time              2  conf.low  CI Lower…    1     85 #> 7    TRTA      Placebo     time              3  estimate  Survival…    1     84 #> 8    TRTA      Placebo     time              3 conf.high  CI Upper…    1     84 #> 9    TRTA      Placebo     time              3  conf.low  CI Lower…    1     84 #> 10   TRTA      Placebo     time              7  estimate  Survival…    1     82 #>    n.event n.censor std.error #> 1        0        1         0 #> 2        0        1         0 #> 3        0        1         0 #> 4        0        1         0 #> 5        0        1         0 #> 6        0        1         0 #> 7        0        2         0 #> 8        0        2         0 #> 9        0        2         0 #> 10       0        1         0 #> ℹ 473 more rows #> ℹ Use `print(n = ...)` to see more rows #> ℹ 3 more variables: fmt_fn, warning, error"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_ttest_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert t-test to ARD — .format_ttest_results","title":"Convert t-test to ARD — .format_ttest_results","text":"Convert t-test ARD","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_ttest_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert t-test to ARD — .format_ttest_results","text":"","code":".format_ttest_results(by = NULL, variable, lst_tidy, paired, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_ttest_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert t-test to ARD — .format_ttest_results","text":"(string) column name variable (string) variable column name lst_tidy (named list) list tidied results constructed eval_capture_conditions(), e.g. eval_capture_conditions(t.test(mtcars$mpg ~ mtcars$) |> broom::tidy()). paired logical indicating whether want paired     t-test. ... passed t.test(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_ttest_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert t-test to ARD — .format_ttest_results","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_ttest_results.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert t-test to ARD — .format_ttest_results","text":"","code":"cardx:::.format_ttest_results(   by = \"ARM\",   variable = \"AGE\",   paired = FALSE,   lst_tidy =     cards::eval_capture_conditions(       stats::t.test(ADSL[[\"AGE\"]] ~ ADSL[[\"ARM\"]], paired = FALSE) |>         broom::tidy()     ) ) #> {cards} data frame: 14 x 9 #>    group1 variable   stat_name stat_label  stat     error #> 1     ARM      AGE    estimate  Mean Dif…       object '… #> 2     ARM      AGE   estimate1  Group 1 …       object '… #> 3     ARM      AGE   estimate2  Group 2 …       object '… #> 4     ARM      AGE   statistic  t Statis…       object '… #> 5     ARM      AGE     p.value    p-value       object '… #> 6     ARM      AGE   parameter  Degrees …       object '… #> 7     ARM      AGE    conf.low  CI Lower…       object '… #> 8     ARM      AGE   conf.high  CI Upper…       object '… #> 9     ARM      AGE      method     method       object '… #> 10    ARM      AGE alternative  alternat…       object '… #> 11    ARM      AGE          mu    H0 Mean     0 object '… #> 12    ARM      AGE      paired  Paired t… FALSE object '… #> 13    ARM      AGE   var.equal  Equal Va… FALSE object '… #> 14    ARM      AGE  conf.level  CI Confi…  0.95 object '… #> ℹ 3 more variables: context, fmt_fn, warning"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_wilcoxtest_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert Wilcoxon test to ARD — .format_wilcoxtest_results","title":"Convert Wilcoxon test to ARD — .format_wilcoxtest_results","text":"Convert Wilcoxon test ARD","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_wilcoxtest_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert Wilcoxon test to ARD — .format_wilcoxtest_results","text":"","code":".format_wilcoxtest_results(by = NULL, variable, lst_tidy, paired, ...)"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_wilcoxtest_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert Wilcoxon test to ARD — .format_wilcoxtest_results","text":"(string) column name variable (string) variable column name lst_tidy (named list) list tidied results constructed eval_capture_conditions(), e.g. eval_capture_conditions(t.test(mtcars$mpg ~ mtcars$) |> broom::tidy()). paired logical indicating whether want paired test. ... passed stats::wilcox.test(...)","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_wilcoxtest_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert Wilcoxon test to ARD — .format_wilcoxtest_results","text":"ARD data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-format_wilcoxtest_results.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert Wilcoxon test to ARD — .format_wilcoxtest_results","text":"","code":"# Pre-processing ADSL to have grouping factor (ARM here) with 2 levels ADSL <- cards::ADSL |>   dplyr::filter(ARM %in% c(\"Placebo\", \"Xanomeline High Dose\")) |>   ard_stats_wilcox_test(by = \"ARM\", variables = \"AGE\")  cardx:::.format_wilcoxtest_results(   by = \"ARM\",   variable = \"AGE\",   paired = FALSE,   lst_tidy =     cards::eval_capture_conditions(       stats::wilcox.test(ADSL[[\"AGE\"]] ~ ADSL[[\"ARM\"]], paired = FALSE) |>         broom::tidy()     ) ) #> {cards} data frame: 12 x 9 #>    group1 variable   stat_name stat_label  stat     error #> 1     ARM      AGE   statistic  X-square…       invalid … #> 2     ARM      AGE     p.value    p-value       invalid … #> 3     ARM      AGE      method     method       invalid … #> 4     ARM      AGE alternative  alternat…       invalid … #> 5     ARM      AGE          mu         mu     0 invalid … #> 6     ARM      AGE      paired  Paired t… FALSE invalid … #> 7     ARM      AGE       exact      exact       invalid … #> 8     ARM      AGE     correct    correct  TRUE invalid … #> 9     ARM      AGE    conf.int   conf.int FALSE invalid … #> 10    ARM      AGE  conf.level  CI Confi…  0.95 invalid … #> 11    ARM      AGE    tol.root   tol.root     0 invalid … #> 12    ARM      AGE digits.rank  digits.r…   Inf invalid … #> ℹ 3 more variables: context, fmt_fn, warning"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-paired_data_pivot_wider.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert long paired data to wide — .paired_data_pivot_wider","title":"Convert long paired data to wide — .paired_data_pivot_wider","text":"Convert long paired data wide","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-paired_data_pivot_wider.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert long paired data to wide — .paired_data_pivot_wider","text":"","code":".paired_data_pivot_wider(data, by, variable, id)"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-paired_data_pivot_wider.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert long paired data to wide — .paired_data_pivot_wider","text":"data (data.frame) data frame one line per subject per group (string) column name variable (string) variable column name id (string) subject id column name","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-paired_data_pivot_wider.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert long paired data to wide — .paired_data_pivot_wider","text":"wide data frame","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-paired_data_pivot_wider.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Convert long paired data to wide — .paired_data_pivot_wider","text":"","code":"cards::ADSL[c(\"ARM\", \"AGE\")] |>   dplyr::filter(ARM %in% c(\"Placebo\", \"Xanomeline High Dose\")) |>   dplyr::mutate(.by = ARM, USUBJID = dplyr::row_number()) |>   dplyr::arrange(USUBJID, ARM) |>   cardx:::.paired_data_pivot_wider(by = \"ARM\", variable = \"AGE\", id = \"USUBJID\") #> # A tibble: 86 × 3 #>    USUBJID   by1   by2 #>      <int> <dbl> <dbl> #>  1       1    63    71 #>  2       2    64    77 #>  3       3    85    81 #>  4       4    52    75 #>  5       5    84    57 #>  6       6    79    56 #>  7       7    81    79 #>  8       8    69    56 #>  9       9    63    61 #> 10      10    81    56 #> # ℹ 76 more rows"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-process_survfit_probs.html","id":null,"dir":"Reference","previous_headings":"","what":"Process Survival Fit For Quantile Estimates — .process_survfit_probs","title":"Process Survival Fit For Quantile Estimates — .process_survfit_probs","text":"Process Survival Fit Quantile Estimates","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-process_survfit_probs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Process Survival Fit For Quantile Estimates — .process_survfit_probs","text":"","code":".process_survfit_probs(x, probs)"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-process_survfit_probs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Process Survival Fit For Quantile Estimates — .process_survfit_probs","text":"x (survival::survfit()) survival::survfit() object. See details. probs (numeric) vector probabilities values (0,1) specifying survival quantiles return.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-process_survfit_probs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Process Survival Fit For Quantile Estimates — .process_survfit_probs","text":"tibble","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-process_survfit_probs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Process Survival Fit For Quantile Estimates — .process_survfit_probs","text":"","code":"survival::survfit(survival::Surv(AVAL, CNSR) ~ TRTA, cards::ADTTE) |>   cardx:::.process_survfit_probs(probs = c(0.25, 0.75)) #> # A tibble: 6 × 6 #>   strata                    estimate conf.low conf.high  prob context          #>   <chr>                        <dbl>    <dbl>     <dbl> <dbl> <chr>            #> 1 TRTA=Placebo                   142       70       181  0.25 survival_survfit #> 2 TRTA=Xanomeline High Dose       44       22       180  0.25 survival_survfit #> 3 TRTA=Xanomeline Low Dose        49       37       180  0.25 survival_survfit #> 4 TRTA=Placebo                   184      183       191  0.75 survival_survfit #> 5 TRTA=Xanomeline High Dose      188      167        NA  0.75 survival_survfit #> 6 TRTA=Xanomeline Low Dose       184      180        NA  0.75 survival_survfit"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-process_survfit_time.html","id":null,"dir":"Reference","previous_headings":"","what":"Process Survival Fit For Time Estimates — .process_survfit_time","title":"Process Survival Fit For Time Estimates — .process_survfit_time","text":"Process Survival Fit Time Estimates","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-process_survfit_time.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Process Survival Fit For Time Estimates — .process_survfit_time","text":"","code":".process_survfit_time(x, times, type)"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-process_survfit_time.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Process Survival Fit For Time Estimates — .process_survfit_time","text":"x (survival::survfit()) survival::survfit() object. See details. times (numeric) vector times return survival probabilities. type (string NULL) type statistic report. Available Kaplan-Meier time estimates , otherwise type ignored. Default NULL. Must one following:","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-process_survfit_time.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Process Survival Fit For Time Estimates — .process_survfit_time","text":"tibble","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-process_survfit_time.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Process Survival Fit For Time Estimates — .process_survfit_time","text":"","code":"survival::survfit(survival::Surv(AVAL, CNSR) ~ TRTA, cards::ADTTE) |>   cardx:::.process_survfit_time(times = c(60, 180), type = \"risk\") #> # A tibble: 6 × 6 #>    time estimate conf.low conf.high strata                    context #>   <dbl>    <dbl>    <dbl>     <dbl> <fct>                     <chr>   #> 1    60    0.107   0.0338     0.175 TRTA=Placebo              risk    #> 2    60    0.306   0.151      0.432 TRTA=Xanomeline High Dose risk    #> 3    60    0.268   0.122      0.390 TRTA=Xanomeline Low Dose  risk    #> 4   180    0.349   0.217      0.459 TRTA=Placebo              risk    #> 5   180    0.738   0.251      0.908 TRTA=Xanomeline High Dose risk    #> 6   180    0.619   0.257      0.805 TRTA=Xanomeline Low Dose  risk"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-strata_normal_quantile.html","id":null,"dir":"Reference","previous_headings":"","what":"Helper Function for the Estimation of Stratified Quantiles — .strata_normal_quantile","title":"Helper Function for the Estimation of Stratified Quantiles — .strata_normal_quantile","text":"function wraps estimation stratified percentiles assume approximation large numbers. necessary case proportions strata unequal.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-strata_normal_quantile.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Helper Function for the Estimation of Stratified Quantiles — .strata_normal_quantile","text":"","code":".strata_normal_quantile(vars, weights, conf.level)"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-strata_normal_quantile.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Helper Function for the Estimation of Stratified Quantiles — .strata_normal_quantile","text":"weights (numeric NULL) weights level strata. NULL, estimated using iterative algorithm minimizes weighted squared length confidence interval. conf.level (numeric) scalar (0, 1) indicating confidence level. Default 0.95","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-strata_normal_quantile.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Helper Function for the Estimation of Stratified Quantiles — .strata_normal_quantile","text":"Stratified quantile.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/cardx/reference/dot-strata_normal_quantile.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Helper Function for the Estimation of Stratified Quantiles — .strata_normal_quantile","text":"","code":"strata_data <- table(data.frame(   \"f1\" = sample(c(TRUE, FALSE), 100, TRUE),   \"f2\" = sample(c(\"x\", \"y\", \"z\"), 100, TRUE),   stringsAsFactors = TRUE )) ns <- colSums(strata_data) ests <- strata_data[\"TRUE\", ] / ns vars <- ests * (1 - ests) / ns weights <- rep(1 / length(ns), length(ns))  cardx:::.strata_normal_quantile(vars, weights, 0.95) #> [1] 1.134584"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-update_weights_strat_wilson.html","id":null,"dir":"Reference","previous_headings":"","what":"Helper Function for the Estimation of Weights for proportion_ci_strat_wilson() — .update_weights_strat_wilson","title":"Helper Function for the Estimation of Weights for proportion_ci_strat_wilson() — .update_weights_strat_wilson","text":"function wraps iteration procedure allows estimate weights proportional strata. assumes minimize weighted squared length confidence interval.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-update_weights_strat_wilson.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Helper Function for the Estimation of Weights for proportion_ci_strat_wilson() — .update_weights_strat_wilson","text":"","code":".update_weights_strat_wilson(   vars,   strata_qnorm,   initial_weights,   n_per_strata,   max.iterations = 50,   conf.level = 0.95,   tol = 0.001 )"},{"path":"https://insightsengineering.github.io/cardx/reference/dot-update_weights_strat_wilson.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Helper Function for the Estimation of Weights for proportion_ci_strat_wilson() — .update_weights_strat_wilson","text":"vars (numeric) normalized proportions strata. strata_qnorm (numeric) initial estimation identical weights quantiles. initial_weights (numeric) initial weights used calculate strata_qnorm. can optimized future need estimate better initial weights. n_per_strata (numeric) number elements strata. max.iterations (count) maximum number iterations tried. Convergence always checked. conf.level (numeric) scalar (0, 1) indicating confidence level. Default 0.95 tol (number) tolerance threshold convergence.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/dot-update_weights_strat_wilson.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Helper Function for the Estimation of Weights for proportion_ci_strat_wilson() — .update_weights_strat_wilson","text":"list 3 elements: n_it, weights, diff_v.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/cardx/reference/dot-update_weights_strat_wilson.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Helper Function for the Estimation of Weights for proportion_ci_strat_wilson() — .update_weights_strat_wilson","text":"","code":"vs <- c(0.011, 0.013, 0.012, 0.014, 0.017, 0.018) sq <- 0.674 ws <- rep(1 / length(vs), length(vs)) ns <- c(22, 18, 17, 17, 14, 12)  cardx:::.update_weights_strat_wilson(vs, sq, ws, ns, 100, 0.95, 0.001) #> $n_it #> [1] 3 #>  #> $weights #> [1] 0.2067191 0.1757727 0.1896962 0.1636346 0.1357615 0.1284160 #>  #> $diff_v #> [1] 1.458717e-01 1.497223e-03 1.442189e-06 #>"},{"path":"https://insightsengineering.github.io/cardx/reference/proportion_ci.html","id":null,"dir":"Reference","previous_headings":"","what":"Functions for Calculating Proportion Confidence Intervals — proportion_ci","title":"Functions for Calculating Proportion Confidence Intervals — proportion_ci","text":"Functions calculate different proportion confidence intervals use ard_proportion().","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/proportion_ci.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Functions for Calculating Proportion Confidence Intervals — proportion_ci","text":"","code":"proportion_ci_wald(x, conf.level = 0.95, correct = FALSE)  proportion_ci_wilson(x, conf.level = 0.95, correct = FALSE)  proportion_ci_clopper_pearson(x, conf.level = 0.95)  proportion_ci_agresti_coull(x, conf.level = 0.95)  proportion_ci_jeffreys(x, conf.level = 0.95)  proportion_ci_strat_wilson(   x,   strata,   weights = NULL,   conf.level = 0.95,   max.iterations = 10L,   correct = FALSE )"},{"path":"https://insightsengineering.github.io/cardx/reference/proportion_ci.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Functions for Calculating Proportion Confidence Intervals — proportion_ci","text":"x vector binary values, .e. logical vector, numeric values c(0, 1) conf.level (numeric) scalar (0, 1) indicating confidence level. Default 0.95 correct (flag) include continuity correction. information, see example stats::prop.test(). strata (factor) variable one level per stratum length x. weights (numeric NULL) weights level strata. NULL, estimated using iterative algorithm minimizes weighted squared length confidence interval. max.iterations (count) maximum number iterations iterative procedure used find estimates optimal weights.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/proportion_ci.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Functions for Calculating Proportion Confidence Intervals — proportion_ci","text":"Confidence interval proportion.","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/proportion_ci.html","id":"functions","dir":"Reference","previous_headings":"","what":"Functions","title":"Functions for Calculating Proportion Confidence Intervals — proportion_ci","text":"proportion_ci_wald(): Calculates Wald interval following usual textbook definition single proportion confidence interval using normal approximation. $$\\hat{p} \\pm z_{\\alpha/2} \\sqrt{\\frac{\\hat{p}(1 - \\hat{p})}{n}}$$ proportion_ci_wilson(): Calculates Wilson interval calling stats::prop.test(). Also referred Wilson score interval. $$\\frac{\\hat{p} + \\frac{z^2_{\\alpha/2}}{2n} \\pm z_{\\alpha/2} \\sqrt{\\frac{\\hat{p}(1 - \\hat{p})}{n} + \\frac{z^2_{\\alpha/2}}{4n^2}}}{1 + \\frac{z^2_{\\alpha/2}}{n}}$$ proportion_ci_clopper_pearson(): Calculates Clopper-Pearson interval calling stats::binom.test(). Also referred exact method. $$ \\left( \\frac{k}{n} \\pm z_{\\alpha/2} \\sqrt{\\frac{\\frac{k}{n}(1-\\frac{k}{n})}{n} + \\frac{z^2_{\\alpha/2}}{4n^2}} \\right) / \\left( 1 + \\frac{z^2_{\\alpha/2}}{n} \\right)$$ proportion_ci_agresti_coull(): Calculates Agresti-Coull interval (created Alan Agresti Brent Coull) (95% CI) adding two successes two failures data using Wald formula construct CI. $$ \\left( \\frac{\\tilde{p} + z^2_{\\alpha/2}/2}{n + z^2_{\\alpha/2}} \\pm z_{\\alpha/2} \\sqrt{\\frac{\\tilde{p}(1 - \\tilde{p})}{n} + \\frac{z^2_{\\alpha/2}}{4n^2}} \\right)$$ proportion_ci_jeffreys(): Calculates Jeffreys interval, equal-tailed interval based non-informative Jeffreys prior binomial proportion. $$\\left( \\text{Beta}\\left(\\frac{k}{2} + \\frac{1}{2}, \\frac{n - k}{2} + \\frac{1}{2}\\right)_\\alpha, \\text{Beta}\\left(\\frac{k}{2} + \\frac{1}{2}, \\frac{n - k}{2} + \\frac{1}{2}\\right)_{1-\\alpha} \\right)$$ proportion_ci_strat_wilson(): Calculates stratified Wilson confidence interval unequal proportions described Xin YA, Su XG. Stratified Wilson Newcombe confidence intervals multiple binomial proportions. Statistics Biopharmaceutical Research. 2010;2(3). $$\\frac{\\hat{p}_j + \\frac{z^2_{\\alpha/2}}{2n_j} \\pm z_{\\alpha/2} \\sqrt{\\frac{\\hat{p}_j(1 - \\hat{p}_j)}{n_j} + \\frac{z^2_{\\alpha/2}}{4n_j^2}}}{1 + \\frac{z^2_{\\alpha/2}}{n_j}}$$","code":""},{"path":"https://insightsengineering.github.io/cardx/reference/proportion_ci.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Functions for Calculating Proportion Confidence Intervals — proportion_ci","text":"","code":"x <- c(   TRUE, TRUE, TRUE, TRUE, TRUE,   FALSE, FALSE, FALSE, FALSE, FALSE )  proportion_ci_wald(x, conf.level = 0.9) #> $N #> [1] 10 #>  #> $estimate #> [1] 0.5 #>  #> $conf.low #> [1] 0.2399258 #>  #> $conf.high #> [1] 0.7600742 #>  #> $conf.level #> [1] 0.9 #>  #> $method #> Wald Confidence Interval without continuity correction #>  proportion_ci_wilson(x, correct = TRUE) #> $N #> [1] 10 #>  #> $conf.level #> [1] 0.95 #>  #> $estimate #>   p  #> 0.5  #>  #> $statistic #> X-squared  #>         0  #>  #> $p.value #> [1] 1 #>  #> $parameter #> df  #>  1  #>  #> $conf.low #> [1] 0.2365931 #>  #> $conf.high #> [1] 0.7634069 #>  #> $method #> Wilson Confidence Interval with continuity correction #>  #> $alternative #> [1] \"two.sided\" #>  proportion_ci_clopper_pearson(x) #> $N #> [1] 10 #>  #> $conf.level #> [1] 0.95 #>  #> $estimate #> probability of success  #>                    0.5  #>  #> $statistic #> number of successes  #>                   5  #>  #> $p.value #> [1] 1 #>  #> $parameter #> number of trials  #>               10  #>  #> $conf.low #> [1] 0.187086 #>  #> $conf.high #> [1] 0.812914 #>  #> $method #> [1] \"Clopper-Pearson Confidence Interval\" #>  #> $alternative #> [1] \"two.sided\" #>  proportion_ci_agresti_coull(x) #> $N #> [1] 10 #>  #> $estimate #> [1] 0.5 #>  #> $conf.low #> [1] 0.2365931 #>  #> $conf.high #> [1] 0.7634069 #>  #> $conf.level #> [1] 0.95 #>  #> $method #> [1] \"Agresti-Coull Confidence Interval\" #>  proportion_ci_jeffreys(x) #> $N #> [1] 10 #>  #> $estimate #> [1] 0.5 #>  #> $conf.low #> [1] 0.2235287 #>  #> $conf.high #> [1] 0.7764713 #>  #> $conf.level #> [1] 0.95 #>  #> $method #> Jeffreys Interval #>  # Stratified Wilson confidence interval with unequal probabilities  set.seed(1) rsp <- sample(c(TRUE, FALSE), 100, TRUE) strata_data <- data.frame(   \"f1\" = sample(c(\"a\", \"b\"), 100, TRUE),   \"f2\" = sample(c(\"x\", \"y\", \"z\"), 100, TRUE),   stringsAsFactors = TRUE ) strata <- interaction(strata_data) n_strata <- ncol(table(rsp, strata)) # Number of strata  proportion_ci_strat_wilson(   x = rsp, strata = strata,   conf.level = 0.90 ) #> $N #> [1] 100 #>  #> $estimate #> [1] 0.49 #>  #> $conf.low #> [1] 0.4072891 #>  #> $conf.high #> [1] 0.5647887 #>  #> $conf.level #> [1] 0.9 #>  #> $weights #>       a.x       b.x       a.y       b.y       a.z       b.z  #> 0.2074199 0.1776464 0.1915610 0.1604678 0.1351096 0.1277952  #>  #> $method #> Stratified Wilson Confidence Interval without continuity correction #>   # Not automatic setting of weights proportion_ci_strat_wilson(   x = rsp, strata = strata,   weights = rep(1 / n_strata, n_strata),   conf.level = 0.90 ) #> $N #> [1] 100 #>  #> $estimate #> [1] 0.49 #>  #> $conf.low #> [1] 0.4190436 #>  #> $conf.high #> [1] 0.5789733 #>  #> $conf.level #> [1] 0.9 #>  #> $method #> Stratified Wilson Confidence Interval without continuity correction #>"},{"path":"https://insightsengineering.github.io/cardx/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. dplyr %>%, all_of, any_of, contains, ends_with, everything, last_col, matches, num_range, one_of, starts_with, ","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/cardx/news/index.html","id":"breaking-changes-0-1-0-9026","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"cardx 0.1.0.9026","text":"Updated function names follow pattern ard_<pkgname>_<fnname>(). Former functions names deprecated. (#106)","code":"ard_ttest()             -> ard_stats_t_test() ard_paired_ttest()      -> ard_stats_paired_t_test() ard_wilcoxtest()        -> ard_stats_wilcox_test() ard_paired_wilcoxtest() -> ard_stats_paired_wilcox_test() ard_chisqtest()         -> ard_stats_chisq_test() ard_fishertest()        -> ard_stats_fisher_test() ard_kruskaltest()       -> ard_stats_kruskal_test() ard_mcnemartest()       -> ard_stats_mcnemar_test() ard_moodtest()          -> ard_stats_mood_test()"},{"path":"https://insightsengineering.github.io/cardx/news/index.html","id":"new-features-0-1-0-9026","dir":"Changelog","previous_headings":"","what":"New Features","title":"cardx 0.1.0.9026","text":"Added following functions calculating Analysis Results Data (ARD). ard_stats_aov() calculating ANOVA results using stats::aov(). (#3) ard_stats_anova() calculating ANOVA results using stats::anova(). (#12) ard_stats_mcnemar_test_long() McNemar’s test long data using stats::mcnemar.test(). ard_aod_wald_test() calculating Wald Tests regression models using aod::wald.test(). (#84) ard_car_anova() calculating ANOVA results using car::Anova(). (#3) ard_stats_oneway_test() calculating ANOVA results using stats::oneway.test(). (#3) ard_effectsize_cohens_d(), ard_effectsize_paired_cohens_d(), ard_effectsize_hedges_g(), ard_effectsize_paired_hedges_g() standardized differences using effectsize::cohens_d() effectsize::hedges_g(). (#50) ard_stats_prop_test() tests proportions using stats::prop.test(). (#64) ard_regression_basic() basic regression models. function focuses matching terms underlying variables names. (#46) ard_smd_smd() calculating standardized mean differences using smd::smd(). (#4) ard_survival_survfit() survival analyses using survival::survfit(). (#43) ard_survey_svycontinuous() calculating univariate summary statistics weighted/survey data using many functions {survey} package. (#68) ard_survey_svychisq() weighted/survey chi-squared test using survey::svychisq(). (#72) ard_survey_svyttest() weighted/survey t-tests using survey::svyttest(). (#70) ard_survey_svyranktest() weighted/survey rank tests using survey::svyranktest(). (#71) ard_car_vif() calculating variance inflation factor using car::vif(). (#10) ard_emmeans_mean_difference() calculating least-squares mean differences using {emmeans} package. (#34) Updated functions ard_stats_t_test(), ard_stats_paired_t_test(), ard_stats_wilcox_test(), ard_stats_paired_wilcox_test(), ard_stats_chisq_test(), ard_stats_fisher_test(), ard_stats_kruskal_test(), ard_stats_mcnemar_test(), ard_stats_mood_test() accept multiple variables . Independent tests calculated variable. variable argument renamed variables. (#77) Updated ard_stats_t_test() ard_stats_wilcox_test() longer require argument, yields central estimates confidence intervals. (#82) Imported cli call environment functions https://github.com/ddsjoberg/standalone/blob/main/R/standalone-cli_call_env.R implemented set_cli_abort_call user-facing functions. (#111) Added ard_survival_survdiff() creating results survival::survdiff(). (#113)","code":""},{"path":"https://insightsengineering.github.io/cardx/news/index.html","id":"cardx-010","dir":"Changelog","previous_headings":"","what":"cardx 0.1.0","title":"cardx 0.1.0","text":"CRAN release: 2024-03-18 Initial release.","code":""}]