diff --git a/404.html b/404.html
index 5fa7fdf..3889505 100644
--- a/404.html
+++ b/404.html
@@ -82,7 +82,7 @@
 
     <footer><div class="pkgdown-footer-left">
   <p></p>
-<p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+<p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/LICENSE-text.html b/LICENSE-text.html
index d3a8c2e..88e187b 100644
--- a/LICENSE-text.html
+++ b/LICENSE-text.html
@@ -56,7 +56,7 @@
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/LICENSE.html b/LICENSE.html
index 8d50aad..9703d82 100644
--- a/LICENSE.html
+++ b/LICENSE.html
@@ -60,7 +60,7 @@
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/apple-touch-icon-120x120.png b/apple-touch-icon-120x120.png
index d4a22d3..eb789c7 100644
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diff --git a/apple-touch-icon-152x152.png b/apple-touch-icon-152x152.png
index ecd01f5..57b703f 100644
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diff --git a/apple-touch-icon-180x180.png b/apple-touch-icon-180x180.png
index b8062b1..743cec1 100644
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diff --git a/apple-touch-icon-60x60.png b/apple-touch-icon-60x60.png
index 428823b..97fa0dc 100644
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diff --git a/apple-touch-icon-76x76.png b/apple-touch-icon-76x76.png
index b95cbe6..78cc592 100644
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diff --git a/apple-touch-icon.png b/apple-touch-icon.png
index 61447ba..619b7dc 100644
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diff --git a/articles/add_functions.html b/articles/add_functions.html
index b73ce1c..7f4b86f 100644
--- a/articles/add_functions.html
+++ b/articles/add_functions.html
@@ -441,7 +441,7 @@ <h3 id="using-building-blocks">Using building-blocks<a class="anchor" aria-label
 
     <footer><div class="pkgdown-footer-left">
   <p></p>
-<p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+<p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/articles/chefStats.html b/articles/chefStats.html
index 06508fd..3e0cd9a 100644
--- a/articles/chefStats.html
+++ b/articles/chefStats.html
@@ -105,7 +105,7 @@ <h2 id="introcution-to-chefstats">Introcution to chefStats<a class="anchor" aria
 
     <footer><div class="pkgdown-footer-left">
   <p></p>
-<p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+<p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/articles/function_types.html b/articles/function_types.html
index fc2c6d3..ab1b7aa 100644
--- a/articles/function_types.html
+++ b/articles/function_types.html
@@ -205,7 +205,7 @@ <h2 id="statistical-method-types-in-chef-and-chefstats">Statistical method types
 
     <footer><div class="pkgdown-footer-left">
   <p></p>
-<p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+<p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/articles/index.html b/articles/index.html
index 84454a2..e91c599 100644
--- a/articles/index.html
+++ b/articles/index.html
@@ -62,7 +62,7 @@ <h3>All vignettes</h3>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/authors.html b/authors.html
index 378f15d..9992496 100644
--- a/authors.html
+++ b/authors.html
@@ -58,6 +58,10 @@ <h2>Authors</h2>
           <p><strong>NOSJ (Nicolai Skov Johnsen)</strong>. Author. 
           </p>
         </li>
+        <li>
+          <p><strong>HSPU (Henrik Sparre Spiegelhauer)</strong>. Author. 
+          </p>
+        </li>
         <li>
           <p><strong>ABIU (Anders Bilgrau)</strong>. Author. 
           </p>
@@ -80,14 +84,14 @@ <h2>Authors</h2>
       <h2 id="citation">Citation</h2>
       <p></p>
 
-      <p>MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen) (2024).
+      <p>MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen) (2024).
 <em>chefStats: Provide methods for different statistics</em>.
 R package version 0.1.1, 
 https://app.codecov.io/github/hta-pharma/chefStats, <a href="https://hta-pharma.github.io/chefStats/">https://hta-pharma.github.io/chefStats/</a>. 
 </p>
       <pre>@Manual{,
   title = {chefStats: Provide methods for different statistics},
-  author = {{MEWP (Matthew Phelps)} and {NOSJ (Nicolai Skov Johnsen)} and {ABIU (Anders Bilgrau)} and {SCQY (scqy)} and {CINO (Christian Haargaard Olsen)}},
+  author = {{MEWP (Matthew Phelps)} and {NOSJ (Nicolai Skov Johnsen)} and {HSPU (Henrik Sparre Spiegelhauer)} and {ABIU (Anders Bilgrau)} and {SCQY (scqy)} and {CINO (Christian Haargaard Olsen)}},
   year = {2024},
   note = {R package version 0.1.1, 
 https://app.codecov.io/github/hta-pharma/chefStats},
@@ -99,7 +103,7 @@ <h2 id="citation">Citation</h2>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/favicon-16x16.png b/favicon-16x16.png
index 27ebdd5..dbe3c03 100644
Binary files a/favicon-16x16.png and b/favicon-16x16.png differ
diff --git a/favicon-32x32.png b/favicon-32x32.png
index 5b50e06..eef2a8b 100644
Binary files a/favicon-32x32.png and b/favicon-32x32.png differ
diff --git a/index.html b/index.html
index 49e01b8..100752b 100644
--- a/index.html
+++ b/index.html
@@ -107,6 +107,7 @@ <h2 data-toc-skip>Developers</h2>
 <ul class="list-unstyled">
 <li>MEWP (Matthew Phelps) <br><small class="roles"> Author </small>  </li>
 <li>NOSJ (Nicolai Skov Johnsen) <br><small class="roles"> Author </small>  </li>
+<li>HSPU (Henrik Sparre Spiegelhauer) <br><small class="roles"> Author </small>  </li>
 <li>ABIU (Anders Bilgrau) <br><small class="roles"> Author </small>  </li>
 <li>SCQY (scqy) <br><small class="roles"> Author </small>  </li>
 <li>CINO (Christian Haargaard Olsen) <br><small class="roles"> Author, maintainer </small>  </li>
@@ -122,7 +123,7 @@ <h2 data-toc-skip>Developers</h2>
 
     <footer><div class="pkgdown-footer-left">
   <p></p>
-<p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+<p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/news/index.html b/news/index.html
index 51629cb..758a873 100644
--- a/news/index.html
+++ b/news/index.html
@@ -62,7 +62,7 @@ <h2 class="pkg-version" data-toc-text="0.1.0" id="chefstats-010">chefStats 0.1.0
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/pkgdown.yml b/pkgdown.yml
index a889b7b..e685070 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -5,7 +5,7 @@ articles:
   add_functions: add_functions.html
   chefStats: chefStats.html
   function_types: function_types.html
-last_built: 2024-04-02T08:53Z
+last_built: 2024-04-02T09:15Z
 urls:
   reference: https://hta-pharma.github.io/chefStats/reference
   article: https://hta-pharma.github.io/chefStats/articles
diff --git a/reference/OR.html b/reference/OR.html
index e053e93..30915a0 100644
--- a/reference/OR.html
+++ b/reference/OR.html
@@ -119,7 +119,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/reference/RD.html b/reference/RD.html
index 9a37a54..499ed17 100644
--- a/reference/RD.html
+++ b/reference/RD.html
@@ -124,7 +124,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/reference/RR.html b/reference/RR.html
index 83c8c7c..ceba5c7 100644
--- a/reference/RR.html
+++ b/reference/RR.html
@@ -119,7 +119,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/reference/barnard_test_.html b/reference/barnard_test_.html
index 45c9e49..e46e975 100644
--- a/reference/barnard_test_.html
+++ b/reference/barnard_test_.html
@@ -87,7 +87,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/reference/breslowdaytest_.html b/reference/breslowdaytest_.html
index 30fe1db..d77f4ab 100644
--- a/reference/breslowdaytest_.html
+++ b/reference/breslowdaytest_.html
@@ -86,7 +86,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/reference/count_set.html b/reference/count_set.html
index 62aefd8..dab6c8f 100644
--- a/reference/count_set.html
+++ b/reference/count_set.html
@@ -112,7 +112,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/reference/demographics_continuous.html b/reference/demographics_continuous.html
index cf415c8..76e9b37 100644
--- a/reference/demographics_continuous.html
+++ b/reference/demographics_continuous.html
@@ -101,7 +101,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/reference/demographics_counts.html b/reference/demographics_counts.html
index 3e8f80e..831d1f5 100644
--- a/reference/demographics_counts.html
+++ b/reference/demographics_counts.html
@@ -106,7 +106,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/reference/hedges_g.html b/reference/hedges_g.html
index ef9b52a..ab5cf11 100644
--- a/reference/hedges_g.html
+++ b/reference/hedges_g.html
@@ -90,7 +90,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/reference/index.html b/reference/index.html
index b43fea3..a904f81 100644
--- a/reference/index.html
+++ b/reference/index.html
@@ -245,7 +245,7 @@ <h2 id="misc">Misc<a class="anchor" aria-label="anchor" href="#misc"></a></h2>
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/reference/make_two_by_two_.html b/reference/make_two_by_two_.html
index 9db81e1..a7a2cef 100644
--- a/reference/make_two_by_two_.html
+++ b/reference/make_two_by_two_.html
@@ -132,7 +132,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/reference/make_two_by_two_by_k_.html b/reference/make_two_by_two_by_k_.html
index 18facc0..2548041 100644
--- a/reference/make_two_by_two_by_k_.html
+++ b/reference/make_two_by_two_by_k_.html
@@ -110,7 +110,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/reference/mean_value.html b/reference/mean_value.html
index 865e6b3..da1fb47 100644
--- a/reference/mean_value.html
+++ b/reference/mean_value.html
@@ -106,7 +106,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
 </div>
 
 <div class="pkgdown-footer-right">
diff --git a/reference/n_event.html b/reference/n_event.html
index 6eb3ea2..ad01206 100644
--- a/reference/n_event.html
+++ b/reference/n_event.html
@@ -97,7 +97,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
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diff --git a/reference/n_event_.html b/reference/n_event_.html
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@@ -82,7 +82,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
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-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
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diff --git a/reference/n_event_100y.html b/reference/n_event_100y.html
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@@ -113,7 +113,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
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-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
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diff --git a/reference/n_sub_.html b/reference/n_sub_.html
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@@ -88,7 +88,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
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-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
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diff --git a/reference/n_subj.html b/reference/n_subj.html
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-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
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diff --git a/reference/n_subj_event.html b/reference/n_subj_event.html
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-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
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diff --git a/reference/n_subj_event_.html b/reference/n_subj_event_.html
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@@ -87,7 +87,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
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diff --git a/reference/obs_time_by_trt.html b/reference/obs_time_by_trt.html
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@@ -91,7 +91,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
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-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
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diff --git a/reference/p_subj_event.html b/reference/p_subj_event.html
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-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
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diff --git a/reference/p_subj_event_.html b/reference/p_subj_event_.html
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-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
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diff --git a/reference/p_subj_event_by_trt.html b/reference/p_subj_event_by_trt.html
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-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
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@@ -135,7 +135,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
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-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
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diff --git a/reference/p_val_interaction.html b/reference/p_val_interaction.html
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-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
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diff --git a/reference/sd_value.html b/reference/sd_value.html
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-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
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diff --git a/reference/use_chefStats.html b/reference/use_chefStats.html
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@@ -92,7 +92,7 @@ <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2
 
 
     <footer><div class="pkgdown-footer-left">
-  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
+  <p></p><p>Developed by MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen).</p>
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diff --git a/search.json b/search.json
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--- a/search.json
+++ b/search.json
@@ -1 +1 @@
-[{"path":"https://hta-pharma.github.io/chefStats/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2024 Novo Nordisk /S, Danish company registration . 24256790 Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://hta-pharma.github.io/chefStats/articles/add_functions.html","id":"walk-through-example","dir":"Articles","previous_headings":"","what":"Walk through example","title":"Adding new functions","text":"show add function n_subj_event(), counts number subjects experiencing event stratification level treatment level, didn’t already exist chefStats. Since function produces number stratification level treatment level, stat_by_strata_by_trt eligible event event stratification “group” (e.g. SEX, AGE, etc) level (“MALE”, “>65”, etc). treatment level (e.g. “TreatmentA”) function definition might look like :","code":"n_subj_event <-   function(dat,            event_index,            cell_index,            subjectid_var,            ... # the `...` are required for all chefStats functions to \"collect\" any unused arguments passed from chef            ) {     # Please see the \"Interface with chef\" section for details on what     # `event_index` and `cell_index`          # `intersect()` provides us with a vector of rows in `dat` that match both     # `event_index` and `cell_index` - aka records that were BOTH eligible to     # have the event (`cell_index`) AND had the event (`event_index`)     index <- intersect(event_index, cell_index)          # Return all matching rows in `dat` where `INDEX_`     # matches `index`.     event_rows <- dat[INDEX_ %in% index]          # `dat` contains event data, meaning subjects can appear more than once if     # they have >1 event, so we need to remove these extra rows to get a proper     # count     event_rows_unique_by_subject <- unique(event_rows, by = subjectid_var)          stat <-   NROW(event_rows_unique_by_subject)      # The return object has to be a data.table object with the following 3     # columns. The `value` column always has to be a double (not an integer)     return(       data.table(         description = \"Number of subjects with events\",         label = \"n_subj_events\",         value = as.double(stat)       )     )    }"},{"path":"https://hta-pharma.github.io/chefStats/articles/add_functions.html","id":"interface-with-chef","dir":"Articles","previous_headings":"","what":"Interface with chef","title":"Adding new functions","text":"statistical functions chefStats called within context chef pipeline. category function determines arguments passed chef function, however arguments passed categories. following table describes arguments passed chefStats function: Arguments always passed chefStats functions  Additionally, function type receives following arguments stat_by_strata_by_trt stat_by_strata_across_trt stat_by_strata_across_trt Additional arguments passed by_strata_by_trt functions Additional arguments passed by_strata_across_trt functions Additional arguments passed across_strata_across_trt functions","code":""},{"path":"https://hta-pharma.github.io/chefStats/articles/add_functions.html","id":"using-building-blocks","dir":"Articles","previous_headings":"","what":"Using building-blocks","title":"Adding new functions","text":"possible, utilize building-block functions making new statistical functions. example, new functions requires 2x2 table, use make_two_by_two_() function instead writing new one. also allows easily write functions collapse several chefStats functions one function call. example, call count_set() one call n_sub(), n_event(), n_subj_event() p_subj_event(). rational combining functions like save compute time, due way chef pipelines constructed. Building block function names always suffixed underscore _ indicate called inside chef pipeline. example, n_event_() building block used make n_event(), n_event_() can also use build functions, count_set(), format ’s output chef pipeline. Conversely, n_event() format output, can use chef pipeline, building block.","code":""},{"path":"https://hta-pharma.github.io/chefStats/articles/chefStats.html","id":"introcution-to-chefstats","dir":"Articles","previous_headings":"","what":"Introcution to chefStats","title":"chefStats","text":"making AMNOG analysis using chef, need pass one summarization/inference functions endpoint. chefStats package makes easier Providing collection fast, validated functions can dropped chef-pipelines “just work” Guiding creation new (validated) functions need one doesn’t yet exist (use_chefStats())","code":""},{"path":"https://hta-pharma.github.io/chefStats/articles/function_types.html","id":"statistical-method-types-in-chef-and-chefstats","dir":"Articles","previous_headings":"","what":"Statistical method types in chef and chefStats","title":"Function types","text":"chef framework categorizes statistical functions three main categories depending operate stratification levels treatment levels. Operations can either done per stratification level treatment level, can operate across levels. Figure 1 shows typical table safety analysis color codes result based function type creates : Figure 1 Table 1 provides description three function types, color coded outputs produce table 1 : Table 1 function type also determines function applied. example figure 1, stat_by_strata_by_trt function called combination stratification level treatment level, well TOTALS treatment level: SEX == “MALE” & TRT == “TreatmentA” SEX == “FEMALE” & TRT == “TreatmentA” SEX == “MALE” & TRT == “TreatmentB” SEX == “FEMALE” & TRT == “TreatmentB” AGE == “<65” & TRT == “TreatmentA” AGE == “>=65” & TRT == “TreatmentA” AGE == “<65” & TRT == “TreatmentB” AGE == “>=65” & TRT == “TreatmentB” TOTAL_ == “total” & TRT == “TreatmentA” TOTAL_ == “total” & TRT == “TreatmentB” Whereas stat_across_strata_across_trt called per stratification “group”, .e.: strata_var == “SEX” strata_var == “AGE”","code":""},{"path":"https://hta-pharma.github.io/chefStats/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"MEWP (Matthew Phelps). Author. NOSJ (Nicolai Skov Johnsen). Author. ABIU (Anders Bilgrau). Author. SCQY (scqy). Author. CINO (Christian Haargaard Olsen). Author, maintainer. Novo Nordisk /S. Copyright holder.","code":""},{"path":"https://hta-pharma.github.io/chefStats/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen) (2024). chefStats: Provide methods different statistics. R package version 0.1.1,  https://app.codecov.io/github/hta-pharma/chefStats, https://hta-pharma.github.io/chefStats/.","code":"@Manual{,   title = {chefStats: Provide methods for different statistics},   author = {{MEWP (Matthew Phelps)} and {NOSJ (Nicolai Skov Johnsen)} and {ABIU (Anders Bilgrau)} and {SCQY (scqy)} and {CINO (Christian Haargaard Olsen)}},   year = {2024},   note = {R package version 0.1.1,  https://app.codecov.io/github/hta-pharma/chefStats},   url = {https://hta-pharma.github.io/chefStats/}, }"},{"path":"https://hta-pharma.github.io/chefStats/index.html","id":"a-library-of-statistical-methods-for-chef-style-amnog-analyses-","dir":"","previous_headings":"","what":"Provide methods for different statistics","title":"Provide methods for different statistics","text":"{chefStats} package aims provide library fast, validated methods use AMNOG analysis created chef package. functions found chefStats designed used chef, may unwieldy use functions independently.","code":""},{"path":"https://hta-pharma.github.io/chefStats/index.html","id":"developer-documentation","dir":"","previous_headings":"","what":"Developer Documentation","title":"Provide methods for different statistics","text":"Please refer {ramnog} general developer documentation. Ramnog Developer Documentation","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/OR.html","id":null,"dir":"Reference","previous_headings":"","what":"Wrapper for Odds Ratio calculation — OR","title":"Wrapper for Odds Ratio calculation — OR","text":"Ensures input statistical function proper format, ensures output formatted need AMNOG workflow.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/OR.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Wrapper for Odds Ratio calculation — OR","text":"","code":"OR(   dat,   event_index,   cell_index,   treatment_var,   treatment_refval,   subjectid_var,   ... )"},{"path":"https://hta-pharma.github.io/chefStats/reference/OR.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Wrapper for Odds Ratio calculation — OR","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. treatment_var character. name treatment variable data. treatment_refval character. reference value treatment variable data. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/OR.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Wrapper for Odds Ratio calculation — OR","text":"data.table containing Odds Ratio statistics.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/RD.html","id":null,"dir":"Reference","previous_headings":"","what":"Wrapper for Risk Difference calculation — RD","title":"Wrapper for Risk Difference calculation — RD","text":"Ensures input statistical function proper format, ensures output formatted need AMNOG workflow.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/RD.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Wrapper for Risk Difference calculation — RD","text":"","code":"RD(   dat,   event_index,   cell_index,   treatment_var,   treatment_refval,   subjectid_var,   as_pct = TRUE,   ... )"},{"path":"https://hta-pharma.github.io/chefStats/reference/RD.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Wrapper for Risk Difference calculation — RD","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. treatment_var character. name treatment variable data. treatment_refval character. reference value treatment variable data. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). as_pct Boolean. ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/RD.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Wrapper for Risk Difference calculation — RD","text":"data.table containing Risk Difference statistics.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/RR.html","id":null,"dir":"Reference","previous_headings":"","what":"Relative Risk calculation — RR","title":"Relative Risk calculation — RR","text":"Ensures input statistical function proper format, ensure output formatted need AMNOG workflow.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/RR.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Relative Risk calculation — RR","text":"","code":"RR(   dat,   event_index,   cell_index,   treatment_var,   treatment_refval,   subjectid_var,   ... )"},{"path":"https://hta-pharma.github.io/chefStats/reference/RR.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Relative Risk calculation — RR","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. treatment_var character. name treatment variable data. treatment_refval character. reference value treatment variable data. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/RR.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Relative Risk calculation — RR","text":"data.table containing Relative Risk statistics.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/barnard_test_.html","id":null,"dir":"Reference","previous_headings":"","what":"Barnards Unconditional Exact Test with trial data — barnard_test_","title":"Barnards Unconditional Exact Test with trial data — barnard_test_","text":"Barnards Unconditional Exact Test trial data","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/barnard_test_.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Barnards Unconditional Exact Test with trial data — barnard_test_","text":"","code":"barnard_test_(two_by_two, verbose = FALSE, safe_mode = TRUE)"},{"path":"https://hta-pharma.github.io/chefStats/reference/barnard_test_.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Barnards Unconditional Exact Test with trial data — barnard_test_","text":"two_by_two two--two table first column contains counts events. verbose Set TRUE want normal output running barnard.test print console. Default FALSE safe_mode invalid input provided, function stop error (default), return NA (safe_mode = FALSE)","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/barnard_test_.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Barnards Unconditional Exact Test with trial data — barnard_test_","text":"2-sided p-value Barnards Unconditional Exact test","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/breslowdaytest_.html","id":null,"dir":"Reference","previous_headings":"","what":"Breslow-Day test — breslowdaytest_","title":"Breslow-Day test — breslowdaytest_","text":"Breslow-Day test","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/breslowdaytest_.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Breslow-Day test — breslowdaytest_","text":"","code":"breslowdaytest_(x, odds_ratio = NA, correct = FALSE)"},{"path":"https://hta-pharma.github.io/chefStats/reference/breslowdaytest_.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Breslow-Day test — breslowdaytest_","text":"x 2x2xK contingency table odds_ratio Odds Ration (default = NA) correct TRUE Tarones correction returned. Default = FALSE.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/breslowdaytest_.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Breslow-Day test — breslowdaytest_","text":"vector three values statistic - Breslow Day test statistic pval - p value evtl. based Tarone test statistic using \\(\\chi^2(K-1)\\) distribution","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/count_set.html","id":null,"dir":"Reference","previous_headings":"","what":"Produce counts of Number of subjects, number of events, number of\nsubjects with events, and proportion of subjects with events — count_set","title":"Produce counts of Number of subjects, number of events, number of\nsubjects with events, and proportion of subjects with events — count_set","text":"short cut - instead calling individual function (n_sub, n_event, n_subj_event, p_subj_event), one call function produce described functions. can useful save compute time inside chef pipeline fewer iterations.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/count_set.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Produce counts of Number of subjects, number of events, number of\nsubjects with events, and proportion of subjects with events — count_set","text":"","code":"count_set(dat, event_index, cell_index, subjectid_var, ...)"},{"path":"https://hta-pharma.github.io/chefStats/reference/count_set.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Produce counts of Number of subjects, number of events, number of\nsubjects with events, and proportion of subjects with events — count_set","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/count_set.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Produce counts of Number of subjects, number of events, number of\nsubjects with events, and proportion of subjects with events — count_set","text":"data.table containing statistical outputs","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/demographics_continuous.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate summary statistics for demographics on a continuous variable — demographics_continuous","title":"Calculate summary statistics for demographics on a continuous variable — demographics_continuous","text":"Calculate set summary statistics (mean, median, sd, min, max, n_non_missing, n_missing) continuous variable demographics endpoints.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/demographics_continuous.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate summary statistics for demographics on a continuous variable — demographics_continuous","text":"","code":"demographics_continuous(dat, event_index, cell_index, subjectid_var, var, ...)"},{"path":"https://hta-pharma.github.io/chefStats/reference/demographics_continuous.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate summary statistics for demographics on a continuous variable — demographics_continuous","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). var character. Name variable analysis data subject statistics. ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/demographics_continuous.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate summary statistics for demographics on a continuous variable — demographics_continuous","text":"data.table containing summary statistics given continuous variable analysis data set.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/demographics_counts.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate basic summary statistics for demographics — demographics_counts","title":"Calculate basic summary statistics for demographics — demographics_counts","text":"Calculate summary statistics (n_non_missing, n_missing) variable demographics endpoints.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/demographics_counts.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate basic summary statistics for demographics — demographics_counts","text":"","code":"demographics_counts(   dat,   cell_index,   subjectid_var,   stratify_by,   strata_var,   ... )"},{"path":"https://hta-pharma.github.io/chefStats/reference/demographics_counts.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate basic summary statistics for demographics — demographics_counts","text":"dat data.table. analysis data set. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). stratify_by character vector. Set variables analysis data stratify . strata_var character. Variable analysis data stratify specific call. ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/demographics_counts.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate basic summary statistics for demographics — demographics_counts","text":"data.table containing summary statistics.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/hedges_g.html","id":null,"dir":"Reference","previous_headings":"","what":"Wrapper to prepare data for Hedges G — hedges_g","title":"Wrapper to prepare data for Hedges G — hedges_g","text":"Wrapper prepare data Hedges G","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/hedges_g.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Wrapper to prepare data for Hedges G — hedges_g","text":"","code":"hedges_g(dat, reference_val, safe_mode = FALSE, ...)"},{"path":"https://hta-pharma.github.io/chefStats/reference/hedges_g.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Wrapper to prepare data for Hedges G — hedges_g","text":"dat data.table. analysis data set. reference_val character. reference value treatment variable data. safe_mode Boolean determining function fail given input calculated (safe_mode = TRUE), silently return NA value (default ... optional arguments ","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/hedges_g.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Wrapper to prepare data for Hedges G — hedges_g","text":"list containing Hedges G statistics.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/make_two_by_two_.html","id":null,"dir":"Reference","previous_headings":"","what":"Make a two-by-two table — make_two_by_two_","title":"Make a two-by-two table — make_two_by_two_","text":"Makes two--two contingency table takes visual form: , B, C, D distinct number subjects satisfying criteria 2x2 cell. observations Treatment value recorded returned.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/make_two_by_two_.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Make a two-by-two table — make_two_by_two_","text":"","code":"make_two_by_two_(   dat,   event_index,   cell_index,   treatment_var,   treatment_refval,   subjectid_var )"},{"path":"https://hta-pharma.github.io/chefStats/reference/make_two_by_two_.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Make a two-by-two table — make_two_by_two_","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. treatment_var character. name treatment variable dat. treatment_refval character. reference value treatment variable dat. subjectid_var character. Name subject identifier variable dat (default \"USUBJID\").","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/make_two_by_two_.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Make a two-by-two table — make_two_by_two_","text":"matrix","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/make_two_by_two_by_k_.html","id":null,"dir":"Reference","previous_headings":"","what":"Make 2x2xk contingency tables from summarized adam data. This function is NOT\ngeneralized — make_two_by_two_by_k_","title":"Make 2x2xk contingency tables from summarized adam data. This function is NOT\ngeneralized — make_two_by_two_by_k_","text":"Make 2x2xk contingency tables summarized adam data. function generalized","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/make_two_by_two_by_k_.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Make 2x2xk contingency tables from summarized adam data. This function is NOT\ngeneralized — make_two_by_two_by_k_","text":"","code":"make_two_by_two_by_k_(   dat,   event_index,   strata_var,   treatment_var,   treatment_refval,   subjectid_var )"},{"path":"https://hta-pharma.github.io/chefStats/reference/make_two_by_two_by_k_.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Make 2x2xk contingency tables from summarized adam data. This function is NOT\ngeneralized — make_two_by_two_by_k_","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. strata_var character. Variable dat stratify specific call. treatment_var character. name treatment variable dat. treatment_refval character. reference value treatment variable dat. subjectid_var character. Name subject identifier variable dat (default \"USUBJID\").","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/make_two_by_two_by_k_.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Make 2x2xk contingency tables from summarized adam data. This function is NOT\ngeneralized — make_two_by_two_by_k_","text":"two--two--k array k represents number subgroups (strata).","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/mean_value.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate mean value — mean_value","title":"Calculate mean value — mean_value","text":"Calculate mean value variable","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/mean_value.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate mean value — mean_value","text":"","code":"mean_value(dat, event_index, cell_index, subjectid_var, var, ...)  mean_value(dat, event_index, cell_index, subjectid_var, var, ...)"},{"path":"https://hta-pharma.github.io/chefStats/reference/mean_value.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate mean value — mean_value","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). var character. Name variable analysis data subject statistics. ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/mean_value.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate mean value — mean_value","text":"data.table containing percentage subjects events treatment. data.table containing mean value.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate number of events by treatment and stratum — n_event","title":"Calculate number of events by treatment and stratum — n_event","text":"Calculate number events treatment stratum.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate number of events by treatment and stratum — n_event","text":"","code":"n_event(dat, event_index, cell_index, subjectid_var, ...)"},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate number of events by treatment and stratum — n_event","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate number of events by treatment and stratum — n_event","text":"data.table containing number events given combination treatment stratum.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event_.html","id":null,"dir":"Reference","previous_headings":"","what":"Building-block: Number of events (multiple events counted multiple times) — n_event_","title":"Building-block: Number of events (multiple events counted multiple times) — n_event_","text":"Building-block: Number events (multiple events counted multiple times)","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event_.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Building-block: Number of events (multiple events counted multiple times) — n_event_","text":"","code":"n_event_(dat, intersect_index)"},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event_.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Building-block: Number of events (multiple events counted multiple times) — n_event_","text":"dat data.table. analysis data set. intersect_index vector intergers referencing rows dat match (1) population analyzed (2) defenition event","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event_.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Building-block: Number of events (multiple events counted multiple times) — n_event_","text":"integer value","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event_100y.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate number of events per 100 years of exposure — n_event_100y","title":"Calculate number of events per 100 years of exposure — n_event_100y","text":"Calculate number events per 100 years exposure","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event_100y.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate number of events per 100 years of exposure — n_event_100y","text":"","code":"n_event_100y(   dat,   event_index,   cell_index,   subjectid_var,   treatment_var,   treatment_value,   ... )"},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event_100y.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate number of events per 100 years of exposure — n_event_100y","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). treatment_var character. Name treatment variable data. treatment_value character. Value treatment variable data. ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event_100y.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate number of events per 100 years of exposure — n_event_100y","text":"data.table containing number events per 100 years exposure.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_sub_.html","id":null,"dir":"Reference","previous_headings":"","what":"Building-block: Number of subjects — n_sub_","title":"Building-block: Number of subjects — n_sub_","text":"Building-block: Number subjects","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_sub_.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Building-block: Number of subjects — n_sub_","text":"","code":"n_sub_(dat, cell_index, subjectid_var)"},{"path":"https://hta-pharma.github.io/chefStats/reference/n_sub_.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Building-block: Number of subjects — n_sub_","text":"dat data.table. analysis data set. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\").","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_sub_.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Building-block: Number of subjects — n_sub_","text":"integer","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate number of subjects by treatment and stratum — n_subj","title":"Calculate number of subjects by treatment and stratum — n_subj","text":"Calculate number subjects treatment stratum.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate number of subjects by treatment and stratum — n_subj","text":"","code":"n_subj(dat, cell_index, subjectid_var, ...)"},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate number of subjects by treatment and stratum — n_subj","text":"dat data.table. analysis data set. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate number of subjects by treatment and stratum — n_subj","text":"data.table containing number subjects given combination treatment stratum.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj_event.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate number of subjects with events by treatment and stratum — n_subj_event","title":"Calculate number of subjects with events by treatment and stratum — n_subj_event","text":"Calculate number subjects events treatment stratum.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj_event.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate number of subjects with events by treatment and stratum — n_subj_event","text":"","code":"n_subj_event(dat, event_index, cell_index, subjectid_var, ...)"},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj_event.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate number of subjects with events by treatment and stratum — n_subj_event","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj_event.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate number of subjects with events by treatment and stratum — n_subj_event","text":"data.table containing number subjects events given combination treatment stratum.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj_event_.html","id":null,"dir":"Reference","previous_headings":"","what":"Building-block: Number of subjects with at least one event — n_subj_event_","title":"Building-block: Number of subjects with at least one event — n_subj_event_","text":"Building-block: Number subjects least one event","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj_event_.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Building-block: Number of subjects with at least one event — n_subj_event_","text":"","code":"n_subj_event_(dat, intersect_index, subjectid_var)"},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj_event_.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Building-block: Number of subjects with at least one event — n_subj_event_","text":"dat data.table. analysis data set. intersect_index vector intergers referencing rows dat match (1) population analyzed (2) defenition event subjectid_var character. Name subject identifier variable data (default \"USUBJID\").","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj_event_.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Building-block: Number of subjects with at least one event — n_subj_event_","text":"interger value","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/obs_time_by_trt.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate observation time by treatment — obs_time_by_trt","title":"Calculate observation time by treatment — obs_time_by_trt","text":"Calculate observation time treatment","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/obs_time_by_trt.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate observation time by treatment — obs_time_by_trt","text":"","code":"obs_time_by_trt(dat, cell_index, subjectid_var, ...)"},{"path":"https://hta-pharma.github.io/chefStats/reference/obs_time_by_trt.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate observation time by treatment — obs_time_by_trt","text":"dat data.table. analysis data set. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/obs_time_by_trt.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate observation time by treatment — obs_time_by_trt","text":"data.table containing observation time treatment.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/p_subj_event.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate percentage of subjects with events by treatment and stratum — p_subj_event","title":"Calculate percentage of subjects with events by treatment and stratum — p_subj_event","text":"Calculate percentage subjects events treatment stratum.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/p_subj_event.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate percentage of subjects with events by treatment and stratum — p_subj_event","text":"","code":"p_subj_event(dat, event_index, cell_index, subjectid_var, ...)"},{"path":"https://hta-pharma.github.io/chefStats/reference/p_subj_event.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate percentage of subjects with events by treatment and stratum — p_subj_event","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/p_subj_event.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate percentage of subjects with events by treatment and stratum — p_subj_event","text":"data.table containing percentage subjects events given combination treatment stratum","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/p_subj_event_.html","id":null,"dir":"Reference","previous_headings":"","what":"Building-block: Proportion of subjects having at least one event — p_subj_event_","title":"Building-block: Proportion of subjects having at least one event — p_subj_event_","text":"Building-block: Proportion subjects least one event","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/p_subj_event_.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Building-block: Proportion of subjects having at least one event — p_subj_event_","text":"","code":"p_subj_event_(dat, cell_index, intersect_index, subjectid_var)"},{"path":"https://hta-pharma.github.io/chefStats/reference/p_subj_event_.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Building-block: Proportion of subjects having at least one event — p_subj_event_","text":"dat data.table. analysis data set. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. intersect_index vector intergers referencing rows dat match (1) population analyzed (2) defenition event subjectid_var character. Name subject identifier variable data (default \"USUBJID\").","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/p_subj_event_.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Building-block: Proportion of subjects having at least one event — p_subj_event_","text":"integer value","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/p_subj_event_by_trt.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate percentage of subjects with events — p_subj_event_by_trt","title":"Calculate percentage of subjects with events — p_subj_event_by_trt","text":"Calculate percentage subjects events treatment strata.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/p_subj_event_by_trt.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate percentage of subjects with events — p_subj_event_by_trt","text":"","code":"p_subj_event_by_trt(   dat,   event_index,   cell_index,   subjectid_var,   treatment_var,   treatment_value,   ... )"},{"path":"https://hta-pharma.github.io/chefStats/reference/p_subj_event_by_trt.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate percentage of subjects with events — p_subj_event_by_trt","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). treatment_var character. Name treatment variable data. treatment_value character. Value treatment variable data. ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/p_subj_event_by_trt.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate percentage of subjects with events — p_subj_event_by_trt","text":"data.table containing percentage subjects events treatment.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/p_val.html","id":null,"dir":"Reference","previous_headings":"","what":"Wrapper for P-value calculations — p_val","title":"Wrapper for P-value calculations — p_val","text":"Ensures input statistical function proper format, enruse output formated need AMNOG workflow.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/p_val.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Wrapper for P-value calculations — p_val","text":"","code":"p_val(   dat,   event_index,   cell_index,   treatment_var,   treatment_refval,   subjectid_var,   safe_mode = FALSE,   threshold_lower = 5,   threshold_upper = 200,   ... )"},{"path":"https://hta-pharma.github.io/chefStats/reference/p_val.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Wrapper for P-value calculations — p_val","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. treatment_var character. name treatment variable data. treatment_refval character. reference value treatment variable data. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). safe_mode Boolean determing function fail given input calculated (safe_mode = TRUE), silently return NA value (default). threshold_lower numeric. Lower threshold limit selecting Fischer vs. Barnard. threshold_upper numeric. Upper threshold limit selecting Fischer vs. Barnard. ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/p_val.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Wrapper for P-value calculations — p_val","text":"data.table containing p-value statistics.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/p_val_interaction.html","id":null,"dir":"Reference","previous_headings":"","what":"Wrapper for P-value of interaction tests — p_val_interaction","title":"Wrapper for P-value of interaction tests — p_val_interaction","text":"Wrapper P-value interaction tests","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/p_val_interaction.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Wrapper for P-value of interaction tests — p_val_interaction","text":"","code":"p_val_interaction(   dat,   event_index,   treatment_var,   treatment_refval,   subjectid_var,   strata_var,   odds_ratio = NA,   correct = FALSE,   ... )"},{"path":"https://hta-pharma.github.io/chefStats/reference/p_val_interaction.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Wrapper for P-value of interaction tests — p_val_interaction","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. treatment_var character. name treatment variable data. treatment_refval character. reference value treatment variable data. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). strata_var character. Variable analysis data stratify specific call. odds_ratio numeric. Odds Ration (default = NA). correct logical. TRUE Tarones correction returned (default = FALSE). ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/p_val_interaction.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Wrapper for P-value of interaction tests — p_val_interaction","text":"data.table containing statistics p-value interaction tests.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/sd_value.html","id":null,"dir":"Reference","previous_headings":"","what":"Standard deviation — sd_value","title":"Standard deviation — sd_value","text":"Standard deviation","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/sd_value.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Standard deviation — sd_value","text":"","code":"sd_value(dat, event_index, cell_index, subjectid_var, var, ...)"},{"path":"https://hta-pharma.github.io/chefStats/reference/sd_value.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standard deviation — sd_value","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). var Character. Name variable analysis data subject statistics. ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/sd_value.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standard deviation — sd_value","text":"data.table containing standard deviation.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/use_chefStats.html","id":null,"dir":"Reference","previous_headings":"","what":"Make new chefStats functions — use_chefStats","title":"Make new chefStats functions — use_chefStats","text":"Make new chefStats functions","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/use_chefStats.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Make new chefStats functions — use_chefStats","text":"","code":"use_chefStats(   fn_name,   fn_type = c(\"stat_by_strata_by_trt\", \"stat_by_strata_across_trt\",     \"stat_across_strata_across_trt\"),   file_name = NULL )"},{"path":"https://hta-pharma.github.io/chefStats/reference/use_chefStats.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Make new chefStats functions — use_chefStats","text":"fn_name Name function. file_name NULL fn_name used make file name fn_type Type statistical function, one stat_by_strata_by_trt, stat_by_strata_across_trt, stat_across_strata_across_trt file_name Name file store function (different fn_name)","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/use_chefStats.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Make new chefStats functions — use_chefStats","text":"Nothing, run side-effect (writes file disk)","code":""},{"path":"https://hta-pharma.github.io/chefStats/news/index.html","id":"chefstats-011","dir":"Changelog","previous_headings":"","what":"chefStats 0.1.1","title":"chefStats 0.1.1","text":"Centralized Git-Actions {ramnog}","code":""},{"path":"https://hta-pharma.github.io/chefStats/news/index.html","id":"chefstats-010","dir":"Changelog","previous_headings":"","what":"chefStats 0.1.0","title":"chefStats 0.1.0","text":"Initial release chefstats Contains initial selection statistical functions use {ramnog} ecosystem.","code":""}]
+[{"path":"https://hta-pharma.github.io/chefStats/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2024 Novo Nordisk /S, Danish company registration . 24256790 Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://hta-pharma.github.io/chefStats/articles/add_functions.html","id":"walk-through-example","dir":"Articles","previous_headings":"","what":"Walk through example","title":"Adding new functions","text":"show add function n_subj_event(), counts number subjects experiencing event stratification level treatment level, didn’t already exist chefStats. Since function produces number stratification level treatment level, stat_by_strata_by_trt eligible event event stratification “group” (e.g. SEX, AGE, etc) level (“MALE”, “>65”, etc). treatment level (e.g. “TreatmentA”) function definition might look like :","code":"n_subj_event <-   function(dat,            event_index,            cell_index,            subjectid_var,            ... # the `...` are required for all chefStats functions to \"collect\" any unused arguments passed from chef            ) {     # Please see the \"Interface with chef\" section for details on what     # `event_index` and `cell_index`          # `intersect()` provides us with a vector of rows in `dat` that match both     # `event_index` and `cell_index` - aka records that were BOTH eligible to     # have the event (`cell_index`) AND had the event (`event_index`)     index <- intersect(event_index, cell_index)          # Return all matching rows in `dat` where `INDEX_`     # matches `index`.     event_rows <- dat[INDEX_ %in% index]          # `dat` contains event data, meaning subjects can appear more than once if     # they have >1 event, so we need to remove these extra rows to get a proper     # count     event_rows_unique_by_subject <- unique(event_rows, by = subjectid_var)          stat <-   NROW(event_rows_unique_by_subject)      # The return object has to be a data.table object with the following 3     # columns. The `value` column always has to be a double (not an integer)     return(       data.table(         description = \"Number of subjects with events\",         label = \"n_subj_events\",         value = as.double(stat)       )     )    }"},{"path":"https://hta-pharma.github.io/chefStats/articles/add_functions.html","id":"interface-with-chef","dir":"Articles","previous_headings":"","what":"Interface with chef","title":"Adding new functions","text":"statistical functions chefStats called within context chef pipeline. category function determines arguments passed chef function, however arguments passed categories. following table describes arguments passed chefStats function: Arguments always passed chefStats functions  Additionally, function type receives following arguments stat_by_strata_by_trt stat_by_strata_across_trt stat_by_strata_across_trt Additional arguments passed by_strata_by_trt functions Additional arguments passed by_strata_across_trt functions Additional arguments passed across_strata_across_trt functions","code":""},{"path":"https://hta-pharma.github.io/chefStats/articles/add_functions.html","id":"using-building-blocks","dir":"Articles","previous_headings":"","what":"Using building-blocks","title":"Adding new functions","text":"possible, utilize building-block functions making new statistical functions. example, new functions requires 2x2 table, use make_two_by_two_() function instead writing new one. also allows easily write functions collapse several chefStats functions one function call. example, call count_set() one call n_sub(), n_event(), n_subj_event() p_subj_event(). rational combining functions like save compute time, due way chef pipelines constructed. Building block function names always suffixed underscore _ indicate called inside chef pipeline. example, n_event_() building block used make n_event(), n_event_() can also use build functions, count_set(), format ’s output chef pipeline. Conversely, n_event() format output, can use chef pipeline, building block.","code":""},{"path":"https://hta-pharma.github.io/chefStats/articles/chefStats.html","id":"introcution-to-chefstats","dir":"Articles","previous_headings":"","what":"Introcution to chefStats","title":"chefStats","text":"making AMNOG analysis using chef, need pass one summarization/inference functions endpoint. chefStats package makes easier Providing collection fast, validated functions can dropped chef-pipelines “just work” Guiding creation new (validated) functions need one doesn’t yet exist (use_chefStats())","code":""},{"path":"https://hta-pharma.github.io/chefStats/articles/function_types.html","id":"statistical-method-types-in-chef-and-chefstats","dir":"Articles","previous_headings":"","what":"Statistical method types in chef and chefStats","title":"Function types","text":"chef framework categorizes statistical functions three main categories depending operate stratification levels treatment levels. Operations can either done per stratification level treatment level, can operate across levels. Figure 1 shows typical table safety analysis color codes result based function type creates : Figure 1 Table 1 provides description three function types, color coded outputs produce table 1 : Table 1 function type also determines function applied. example figure 1, stat_by_strata_by_trt function called combination stratification level treatment level, well TOTALS treatment level: SEX == “MALE” & TRT == “TreatmentA” SEX == “FEMALE” & TRT == “TreatmentA” SEX == “MALE” & TRT == “TreatmentB” SEX == “FEMALE” & TRT == “TreatmentB” AGE == “<65” & TRT == “TreatmentA” AGE == “>=65” & TRT == “TreatmentA” AGE == “<65” & TRT == “TreatmentB” AGE == “>=65” & TRT == “TreatmentB” TOTAL_ == “total” & TRT == “TreatmentA” TOTAL_ == “total” & TRT == “TreatmentB” Whereas stat_across_strata_across_trt called per stratification “group”, .e.: strata_var == “SEX” strata_var == “AGE”","code":""},{"path":"https://hta-pharma.github.io/chefStats/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"MEWP (Matthew Phelps). Author. NOSJ (Nicolai Skov Johnsen). Author. HSPU (Henrik Sparre Spiegelhauer). Author. ABIU (Anders Bilgrau). Author. SCQY (scqy). Author. CINO (Christian Haargaard Olsen). Author, maintainer. Novo Nordisk /S. Copyright holder.","code":""},{"path":"https://hta-pharma.github.io/chefStats/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"MEWP (Matthew Phelps), NOSJ (Nicolai Skov Johnsen), HSPU (Henrik Sparre Spiegelhauer), ABIU (Anders Bilgrau), SCQY (scqy), CINO (Christian Haargaard Olsen) (2024). chefStats: Provide methods different statistics. R package version 0.1.1,  https://app.codecov.io/github/hta-pharma/chefStats, https://hta-pharma.github.io/chefStats/.","code":"@Manual{,   title = {chefStats: Provide methods for different statistics},   author = {{MEWP (Matthew Phelps)} and {NOSJ (Nicolai Skov Johnsen)} and {HSPU (Henrik Sparre Spiegelhauer)} and {ABIU (Anders Bilgrau)} and {SCQY (scqy)} and {CINO (Christian Haargaard Olsen)}},   year = {2024},   note = {R package version 0.1.1,  https://app.codecov.io/github/hta-pharma/chefStats},   url = {https://hta-pharma.github.io/chefStats/}, }"},{"path":"https://hta-pharma.github.io/chefStats/index.html","id":"a-library-of-statistical-methods-for-chef-style-amnog-analyses-","dir":"","previous_headings":"","what":"Provide methods for different statistics","title":"Provide methods for different statistics","text":"{chefStats} package aims provide library fast, validated methods use AMNOG analysis created chef package. functions found chefStats designed used chef, may unwieldy use functions independently.","code":""},{"path":"https://hta-pharma.github.io/chefStats/index.html","id":"developer-documentation","dir":"","previous_headings":"","what":"Developer Documentation","title":"Provide methods for different statistics","text":"Please refer {ramnog} general developer documentation. Ramnog Developer Documentation","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/OR.html","id":null,"dir":"Reference","previous_headings":"","what":"Wrapper for Odds Ratio calculation — OR","title":"Wrapper for Odds Ratio calculation — OR","text":"Ensures input statistical function proper format, ensures output formatted need AMNOG workflow.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/OR.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Wrapper for Odds Ratio calculation — OR","text":"","code":"OR(   dat,   event_index,   cell_index,   treatment_var,   treatment_refval,   subjectid_var,   ... )"},{"path":"https://hta-pharma.github.io/chefStats/reference/OR.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Wrapper for Odds Ratio calculation — OR","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. treatment_var character. name treatment variable data. treatment_refval character. reference value treatment variable data. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/OR.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Wrapper for Odds Ratio calculation — OR","text":"data.table containing Odds Ratio statistics.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/RD.html","id":null,"dir":"Reference","previous_headings":"","what":"Wrapper for Risk Difference calculation — RD","title":"Wrapper for Risk Difference calculation — RD","text":"Ensures input statistical function proper format, ensures output formatted need AMNOG workflow.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/RD.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Wrapper for Risk Difference calculation — RD","text":"","code":"RD(   dat,   event_index,   cell_index,   treatment_var,   treatment_refval,   subjectid_var,   as_pct = TRUE,   ... )"},{"path":"https://hta-pharma.github.io/chefStats/reference/RD.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Wrapper for Risk Difference calculation — RD","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. treatment_var character. name treatment variable data. treatment_refval character. reference value treatment variable data. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). as_pct Boolean. ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/RD.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Wrapper for Risk Difference calculation — RD","text":"data.table containing Risk Difference statistics.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/RR.html","id":null,"dir":"Reference","previous_headings":"","what":"Relative Risk calculation — RR","title":"Relative Risk calculation — RR","text":"Ensures input statistical function proper format, ensure output formatted need AMNOG workflow.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/RR.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Relative Risk calculation — RR","text":"","code":"RR(   dat,   event_index,   cell_index,   treatment_var,   treatment_refval,   subjectid_var,   ... )"},{"path":"https://hta-pharma.github.io/chefStats/reference/RR.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Relative Risk calculation — RR","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. treatment_var character. name treatment variable data. treatment_refval character. reference value treatment variable data. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/RR.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Relative Risk calculation — RR","text":"data.table containing Relative Risk statistics.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/barnard_test_.html","id":null,"dir":"Reference","previous_headings":"","what":"Barnards Unconditional Exact Test with trial data — barnard_test_","title":"Barnards Unconditional Exact Test with trial data — barnard_test_","text":"Barnards Unconditional Exact Test trial data","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/barnard_test_.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Barnards Unconditional Exact Test with trial data — barnard_test_","text":"","code":"barnard_test_(two_by_two, verbose = FALSE, safe_mode = TRUE)"},{"path":"https://hta-pharma.github.io/chefStats/reference/barnard_test_.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Barnards Unconditional Exact Test with trial data — barnard_test_","text":"two_by_two two--two table first column contains counts events. verbose Set TRUE want normal output running barnard.test print console. Default FALSE safe_mode invalid input provided, function stop error (default), return NA (safe_mode = FALSE)","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/barnard_test_.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Barnards Unconditional Exact Test with trial data — barnard_test_","text":"2-sided p-value Barnards Unconditional Exact test","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/breslowdaytest_.html","id":null,"dir":"Reference","previous_headings":"","what":"Breslow-Day test — breslowdaytest_","title":"Breslow-Day test — breslowdaytest_","text":"Breslow-Day test","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/breslowdaytest_.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Breslow-Day test — breslowdaytest_","text":"","code":"breslowdaytest_(x, odds_ratio = NA, correct = FALSE)"},{"path":"https://hta-pharma.github.io/chefStats/reference/breslowdaytest_.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Breslow-Day test — breslowdaytest_","text":"x 2x2xK contingency table odds_ratio Odds Ration (default = NA) correct TRUE Tarones correction returned. Default = FALSE.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/breslowdaytest_.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Breslow-Day test — breslowdaytest_","text":"vector three values statistic - Breslow Day test statistic pval - p value evtl. based Tarone test statistic using \\(\\chi^2(K-1)\\) distribution","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/count_set.html","id":null,"dir":"Reference","previous_headings":"","what":"Produce counts of Number of subjects, number of events, number of\nsubjects with events, and proportion of subjects with events — count_set","title":"Produce counts of Number of subjects, number of events, number of\nsubjects with events, and proportion of subjects with events — count_set","text":"short cut - instead calling individual function (n_sub, n_event, n_subj_event, p_subj_event), one call function produce described functions. can useful save compute time inside chef pipeline fewer iterations.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/count_set.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Produce counts of Number of subjects, number of events, number of\nsubjects with events, and proportion of subjects with events — count_set","text":"","code":"count_set(dat, event_index, cell_index, subjectid_var, ...)"},{"path":"https://hta-pharma.github.io/chefStats/reference/count_set.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Produce counts of Number of subjects, number of events, number of\nsubjects with events, and proportion of subjects with events — count_set","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/count_set.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Produce counts of Number of subjects, number of events, number of\nsubjects with events, and proportion of subjects with events — count_set","text":"data.table containing statistical outputs","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/demographics_continuous.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate summary statistics for demographics on a continuous variable — demographics_continuous","title":"Calculate summary statistics for demographics on a continuous variable — demographics_continuous","text":"Calculate set summary statistics (mean, median, sd, min, max, n_non_missing, n_missing) continuous variable demographics endpoints.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/demographics_continuous.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate summary statistics for demographics on a continuous variable — demographics_continuous","text":"","code":"demographics_continuous(dat, event_index, cell_index, subjectid_var, var, ...)"},{"path":"https://hta-pharma.github.io/chefStats/reference/demographics_continuous.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate summary statistics for demographics on a continuous variable — demographics_continuous","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). var character. Name variable analysis data subject statistics. ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/demographics_continuous.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate summary statistics for demographics on a continuous variable — demographics_continuous","text":"data.table containing summary statistics given continuous variable analysis data set.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/demographics_counts.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate basic summary statistics for demographics — demographics_counts","title":"Calculate basic summary statistics for demographics — demographics_counts","text":"Calculate summary statistics (n_non_missing, n_missing) variable demographics endpoints.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/demographics_counts.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate basic summary statistics for demographics — demographics_counts","text":"","code":"demographics_counts(   dat,   cell_index,   subjectid_var,   stratify_by,   strata_var,   ... )"},{"path":"https://hta-pharma.github.io/chefStats/reference/demographics_counts.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate basic summary statistics for demographics — demographics_counts","text":"dat data.table. analysis data set. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). stratify_by character vector. Set variables analysis data stratify . strata_var character. Variable analysis data stratify specific call. ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/demographics_counts.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate basic summary statistics for demographics — demographics_counts","text":"data.table containing summary statistics.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/hedges_g.html","id":null,"dir":"Reference","previous_headings":"","what":"Wrapper to prepare data for Hedges G — hedges_g","title":"Wrapper to prepare data for Hedges G — hedges_g","text":"Wrapper prepare data Hedges G","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/hedges_g.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Wrapper to prepare data for Hedges G — hedges_g","text":"","code":"hedges_g(dat, reference_val, safe_mode = FALSE, ...)"},{"path":"https://hta-pharma.github.io/chefStats/reference/hedges_g.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Wrapper to prepare data for Hedges G — hedges_g","text":"dat data.table. analysis data set. reference_val character. reference value treatment variable data. safe_mode Boolean determining function fail given input calculated (safe_mode = TRUE), silently return NA value (default ... optional arguments ","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/hedges_g.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Wrapper to prepare data for Hedges G — hedges_g","text":"list containing Hedges G statistics.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/make_two_by_two_.html","id":null,"dir":"Reference","previous_headings":"","what":"Make a two-by-two table — make_two_by_two_","title":"Make a two-by-two table — make_two_by_two_","text":"Makes two--two contingency table takes visual form: , B, C, D distinct number subjects satisfying criteria 2x2 cell. observations Treatment value recorded returned.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/make_two_by_two_.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Make a two-by-two table — make_two_by_two_","text":"","code":"make_two_by_two_(   dat,   event_index,   cell_index,   treatment_var,   treatment_refval,   subjectid_var )"},{"path":"https://hta-pharma.github.io/chefStats/reference/make_two_by_two_.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Make a two-by-two table — make_two_by_two_","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. treatment_var character. name treatment variable dat. treatment_refval character. reference value treatment variable dat. subjectid_var character. Name subject identifier variable dat (default \"USUBJID\").","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/make_two_by_two_.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Make a two-by-two table — make_two_by_two_","text":"matrix","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/make_two_by_two_by_k_.html","id":null,"dir":"Reference","previous_headings":"","what":"Make 2x2xk contingency tables from summarized adam data. This function is NOT\ngeneralized — make_two_by_two_by_k_","title":"Make 2x2xk contingency tables from summarized adam data. This function is NOT\ngeneralized — make_two_by_two_by_k_","text":"Make 2x2xk contingency tables summarized adam data. function generalized","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/make_two_by_two_by_k_.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Make 2x2xk contingency tables from summarized adam data. This function is NOT\ngeneralized — make_two_by_two_by_k_","text":"","code":"make_two_by_two_by_k_(   dat,   event_index,   strata_var,   treatment_var,   treatment_refval,   subjectid_var )"},{"path":"https://hta-pharma.github.io/chefStats/reference/make_two_by_two_by_k_.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Make 2x2xk contingency tables from summarized adam data. This function is NOT\ngeneralized — make_two_by_two_by_k_","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. strata_var character. Variable dat stratify specific call. treatment_var character. name treatment variable dat. treatment_refval character. reference value treatment variable dat. subjectid_var character. Name subject identifier variable dat (default \"USUBJID\").","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/make_two_by_two_by_k_.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Make 2x2xk contingency tables from summarized adam data. This function is NOT\ngeneralized — make_two_by_two_by_k_","text":"two--two--k array k represents number subgroups (strata).","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/mean_value.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate mean value — mean_value","title":"Calculate mean value — mean_value","text":"Calculate mean value variable","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/mean_value.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate mean value — mean_value","text":"","code":"mean_value(dat, event_index, cell_index, subjectid_var, var, ...)  mean_value(dat, event_index, cell_index, subjectid_var, var, ...)"},{"path":"https://hta-pharma.github.io/chefStats/reference/mean_value.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate mean value — mean_value","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). var character. Name variable analysis data subject statistics. ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/mean_value.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate mean value — mean_value","text":"data.table containing percentage subjects events treatment. data.table containing mean value.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate number of events by treatment and stratum — n_event","title":"Calculate number of events by treatment and stratum — n_event","text":"Calculate number events treatment stratum.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate number of events by treatment and stratum — n_event","text":"","code":"n_event(dat, event_index, cell_index, subjectid_var, ...)"},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate number of events by treatment and stratum — n_event","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate number of events by treatment and stratum — n_event","text":"data.table containing number events given combination treatment stratum.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event_.html","id":null,"dir":"Reference","previous_headings":"","what":"Building-block: Number of events (multiple events counted multiple times) — n_event_","title":"Building-block: Number of events (multiple events counted multiple times) — n_event_","text":"Building-block: Number events (multiple events counted multiple times)","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event_.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Building-block: Number of events (multiple events counted multiple times) — n_event_","text":"","code":"n_event_(dat, intersect_index)"},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event_.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Building-block: Number of events (multiple events counted multiple times) — n_event_","text":"dat data.table. analysis data set. intersect_index vector intergers referencing rows dat match (1) population analyzed (2) defenition event","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event_.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Building-block: Number of events (multiple events counted multiple times) — n_event_","text":"integer value","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event_100y.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate number of events per 100 years of exposure — n_event_100y","title":"Calculate number of events per 100 years of exposure — n_event_100y","text":"Calculate number events per 100 years exposure","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event_100y.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate number of events per 100 years of exposure — n_event_100y","text":"","code":"n_event_100y(   dat,   event_index,   cell_index,   subjectid_var,   treatment_var,   treatment_value,   ... )"},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event_100y.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate number of events per 100 years of exposure — n_event_100y","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). treatment_var character. Name treatment variable data. treatment_value character. Value treatment variable data. ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_event_100y.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate number of events per 100 years of exposure — n_event_100y","text":"data.table containing number events per 100 years exposure.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_sub_.html","id":null,"dir":"Reference","previous_headings":"","what":"Building-block: Number of subjects — n_sub_","title":"Building-block: Number of subjects — n_sub_","text":"Building-block: Number subjects","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_sub_.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Building-block: Number of subjects — n_sub_","text":"","code":"n_sub_(dat, cell_index, subjectid_var)"},{"path":"https://hta-pharma.github.io/chefStats/reference/n_sub_.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Building-block: Number of subjects — n_sub_","text":"dat data.table. analysis data set. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\").","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_sub_.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Building-block: Number of subjects — n_sub_","text":"integer","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate number of subjects by treatment and stratum — n_subj","title":"Calculate number of subjects by treatment and stratum — n_subj","text":"Calculate number subjects treatment stratum.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate number of subjects by treatment and stratum — n_subj","text":"","code":"n_subj(dat, cell_index, subjectid_var, ...)"},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate number of subjects by treatment and stratum — n_subj","text":"dat data.table. analysis data set. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate number of subjects by treatment and stratum — n_subj","text":"data.table containing number subjects given combination treatment stratum.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj_event.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate number of subjects with events by treatment and stratum — n_subj_event","title":"Calculate number of subjects with events by treatment and stratum — n_subj_event","text":"Calculate number subjects events treatment stratum.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj_event.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate number of subjects with events by treatment and stratum — n_subj_event","text":"","code":"n_subj_event(dat, event_index, cell_index, subjectid_var, ...)"},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj_event.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate number of subjects with events by treatment and stratum — n_subj_event","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj_event.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate number of subjects with events by treatment and stratum — n_subj_event","text":"data.table containing number subjects events given combination treatment stratum.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj_event_.html","id":null,"dir":"Reference","previous_headings":"","what":"Building-block: Number of subjects with at least one event — n_subj_event_","title":"Building-block: Number of subjects with at least one event — n_subj_event_","text":"Building-block: Number subjects least one event","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj_event_.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Building-block: Number of subjects with at least one event — n_subj_event_","text":"","code":"n_subj_event_(dat, intersect_index, subjectid_var)"},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj_event_.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Building-block: Number of subjects with at least one event — n_subj_event_","text":"dat data.table. analysis data set. intersect_index vector intergers referencing rows dat match (1) population analyzed (2) defenition event subjectid_var character. Name subject identifier variable data (default \"USUBJID\").","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/n_subj_event_.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Building-block: Number of subjects with at least one event — n_subj_event_","text":"interger value","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/obs_time_by_trt.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate observation time by treatment — obs_time_by_trt","title":"Calculate observation time by treatment — obs_time_by_trt","text":"Calculate observation time treatment","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/obs_time_by_trt.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate observation time by treatment — obs_time_by_trt","text":"","code":"obs_time_by_trt(dat, cell_index, subjectid_var, ...)"},{"path":"https://hta-pharma.github.io/chefStats/reference/obs_time_by_trt.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate observation time by treatment — obs_time_by_trt","text":"dat data.table. analysis data set. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/obs_time_by_trt.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate observation time by treatment — obs_time_by_trt","text":"data.table containing observation time treatment.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/p_subj_event.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate percentage of subjects with events by treatment and stratum — p_subj_event","title":"Calculate percentage of subjects with events by treatment and stratum — p_subj_event","text":"Calculate percentage subjects events treatment stratum.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/p_subj_event.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate percentage of subjects with events by treatment and stratum — p_subj_event","text":"","code":"p_subj_event(dat, event_index, cell_index, subjectid_var, ...)"},{"path":"https://hta-pharma.github.io/chefStats/reference/p_subj_event.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate percentage of subjects with events by treatment and stratum — p_subj_event","text":"dat data.table. analysis data set. event_index vector integers index rows dat match definition 'event'. Matching done via INDEX_ column dat. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. subjectid_var character. Name subject identifier variable data (default \"USUBJID\"). ... Optional parameters.","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/p_subj_event.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate percentage of subjects with events by treatment and stratum — p_subj_event","text":"data.table containing percentage subjects events given combination treatment stratum","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/p_subj_event_.html","id":null,"dir":"Reference","previous_headings":"","what":"Building-block: Proportion of subjects having at least one event — p_subj_event_","title":"Building-block: Proportion of subjects having at least one event — p_subj_event_","text":"Building-block: Proportion subjects least one event","code":""},{"path":"https://hta-pharma.github.io/chefStats/reference/p_subj_event_.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Building-block: Proportion of subjects having at least one event — p_subj_event_","text":"","code":"p_subj_event_(dat, cell_index, intersect_index, subjectid_var)"},{"path":"https://hta-pharma.github.io/chefStats/reference/p_subj_event_.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Building-block: Proportion of subjects having at least one event — p_subj_event_","text":"dat data.table. analysis data set. cell_index vector integers referencing rows dat (specified INDEX_ column dat) match population analyzed. See \"Endpoint Events\" vignette ramnog information. intersect_index vector intergers referencing rows dat match (1) population analyzed (2) defenition event subjectid_var character. 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