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Linear-models-overview.html

@@ -3926,15 +3926,15 @@ <h3 class="anchored">Note</h3>
 <tbody>
 <tr class="odd">
 <td style="text-align: left;">full</td>
-<td style="text-align: right;">6.803</td>
+<td style="text-align: right;">7.055</td>
 <td style="text-align: right;">0.4805</td>
 <td style="text-align: right;">0.3831</td>
 <td style="text-align: right;">5.956</td>
 <td style="text-align: right;">-61.84</td>
 </tr>
 <tr class="even">
 <td style="text-align: left;">reduced</td>
-<td style="text-align: right;">6.657</td>
+<td style="text-align: right;">6.642</td>
 <td style="text-align: right;">0.4454</td>
 <td style="text-align: right;">0.3802</td>
 <td style="text-align: right;">5.971</td>
@@ -4071,10 +4071,10 @@ <h3 class="anchored">Note</h3>
 <details class="code-fold"><summary>Show R code</summary><div class="sourceCode" id="cb105"><pre class="downlit sourceCode r code-with-copy"><code class="sourceCode R"><span><span class="fu"><a href="https://rdrr.io/r/stats/coef.html">coef</a></span><span class="op">(</span><span class="va">cvfit</span>, s <span class="op">=</span> <span class="st">"lambda.1se"</span><span class="op">)</span></span>
 <span><span class="co">#&gt; 4 x 1 sparse Matrix of class "dgCMatrix"</span></span>
 <span><span class="co">#&gt;                  s1</span></span>
-<span><span class="co">#&gt; (Intercept) 34.2044</span></span>
+<span><span class="co">#&gt; (Intercept) 34.1090</span></span>
 <span><span class="co">#&gt; age          .     </span></span>
-<span><span class="co">#&gt; weight      -0.0926</span></span>
-<span><span class="co">#&gt; protein      0.8582</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<span><span class="co">#&gt; weight      -0.1041</span></span>
+<span><span class="co">#&gt; protein      0.9441</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </details>
 </div>
 </section></section></section><section id="categorical-covariates-with-more-than-two-levels" class="level2" data-number="2.10"><h2 data-number="2.10" class="anchored" data-anchor-id="categorical-covariates-with-more-than-two-levels">

count-regression.html

@@ -395,9 +395,12 @@
   <li><a href="#quasipoisson" id="toc-quasipoisson" class="nav-link" data-scroll-target="#quasipoisson"><span class="header-section-number">4.6.2</span> Quasipoisson</a></li>
   </ul>
 </li>
-  <li><a href="#example-needle-sharing" id="toc-example-needle-sharing" class="nav-link" data-scroll-target="#example-needle-sharing"><span class="header-section-number">4.7</span> Example: needle-sharing</a></li>
-  <li><a href="#covariate-counts" id="toc-covariate-counts" class="nav-link" data-scroll-target="#covariate-counts"><span class="header-section-number">4.8</span> Covariate counts:</a></li>
-  <li><a href="#model" id="toc-model" class="nav-link" data-scroll-target="#model"><span class="header-section-number">4.9</span> model</a></li>
+  <li>
+<a href="#example-needle-sharing" id="toc-example-needle-sharing" class="nav-link" data-scroll-target="#example-needle-sharing"><span class="header-section-number">4.7</span> Example: needle-sharing</a>
+  <ul class="collapse">
+<li><a href="#models" id="toc-models" class="nav-link" data-scroll-target="#models"><span class="header-section-number">4.7.1</span> models</a></li>
+  </ul>
+</li>
   </ul><div class="toc-actions"><ul><li><a href="https://github.com/d-morrison/rme/edit/main/count-regression.qmd" class="toc-action"><i class="bi bi-github"></i>Edit this page</a></li><li><a href="https://github.com/d-morrison/rme/issues/new" class="toc-action"><i class="bi empty"></i>Report an issue</a></li></ul></div></nav>
     </div>
 <!-- main -->
@@ -750,8 +753,7 @@
 </div>
 </div>
 </div>
-</section><section id="covariate-counts" class="level2" data-number="4.8"><h2 data-number="4.8" class="anchored" data-anchor-id="covariate-counts">
-<span class="header-section-number">4.8</span> Covariate counts:</h2>
+<section id="covariate-counts" class="level4"><h4 class="anchored" data-anchor-id="covariate-counts">Covariate counts:</h4>
 <div class="cell">
 <details class="code-fold"><summary>Show R code</summary><div class="sourceCode" id="cb5"><pre class="downlit sourceCode r code-with-copy"><code class="sourceCode R"><span><span class="va">needles</span> <span class="op">|&gt;</span> </span>
 <span>  <span class="fu">dplyr</span><span class="fu">::</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html">select</a></span><span class="op">(</span><span class="va">sex</span>, <span class="va">homeless</span>, <span class="va">polydrug</span><span class="op">)</span> <span class="op">|&gt;</span> </span>
@@ -768,8 +770,8 @@
 <span><span class="va">needles</span> <span class="op">=</span> <span class="va">needles</span> <span class="op">|&gt;</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span><span class="op">(</span><span class="va">sex</span> <span class="op">!=</span> <span class="st">"Trans"</span><span class="op">)</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </details>
 </div>
-</section><section id="model" class="level2 smaller" data-number="4.9"><h2 class="smaller anchored" data-number="4.9" data-anchor-id="model">
-<span class="header-section-number">4.9</span> model</h2>
+</section><section id="models" class="level3 smaller" data-number="4.7.1"><h3 class="smaller anchored" data-number="4.7.1" data-anchor-id="models">
+<span class="header-section-number">4.7.1</span> models</h3>
 <div class="cell">
 <details class="code-fold"><summary>Show R code</summary><div class="sourceCode" id="cb7"><pre class="downlit sourceCode r code-with-copy"><code class="sourceCode R"><span><span class="va">glm1</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/stats/glm.html">glm</a></span><span class="op">(</span></span>
 <span>  data <span class="op">=</span> <span class="va">needles</span>,</span>
@@ -1275,7 +1277,7 @@
 Vittinghoff, Eric, David V Glidden, Stephen C Shiboski, and Charles E McCulloch. 2012. <em>Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models</em>. 2nd ed. Springer. <a href="https://doi.org/10.1007/978-1-4614-1353-0">https://doi.org/10.1007/978-1-4614-1353-0</a>.
 </div>
 </div>
-</section></section></main><!-- /main --><script id="quarto-html-after-body" type="application/javascript">
+</section></section></section></main><!-- /main --><script id="quarto-html-after-body" type="application/javascript">
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index.html

@@ -395,7 +395,7 @@ <h2 id="toc-title">Table of contents</h2>
     <div>
     <div class="quarto-title-meta-heading">Published</div>
     <div class="quarto-title-meta-contents">
-      <p class="date">Last modified: 2024-05-21: 13:20:45 (PM)</p>
+      <p class="date">Last modified: 2024-05-21: 13:48:43 (PM)</p>
     </div>
   </div>
 
@@ -520,7 +520,7 @@ <h2 class="unnumbered anchored" data-anchor-id="license">License</h2>
 McCullagh, Peter, and J. A. Nelder. 1989. <em>Generalized Linear Models</em>. 2nd ed. Routledge. <a href="https://www.utstat.toronto.edu/~brunner/oldclass/2201s11/readings/glmbook.pdf">https://www.utstat.toronto.edu/~brunner/oldclass/2201s11/readings/glmbook.pdf</a>.
 </div>
 <div id="ref-moore2016applied" class="csl-entry" role="listitem">
-Moore, Dirk F. 2016. <em>Applied Survival Analysis Using r</em>. Vol. 473. Springer.
+Moore, Dirk F. 2016. <em>Applied Survival Analysis Using r</em>. Vol. 473. Springer. <a href="https://doi.org/10.1007/978-3-319-31245-3">https://doi.org/10.1007/978-3-319-31245-3</a>.
 </div>
 <div id="ref-NahhasIRMPHR" class="csl-entry" role="listitem">
 Nahhas, Ramzi W. n.d. <em>Introduction to Regression Methods for Public Health Using r</em>. CRC Press. <a href="https://www.bookdown.org/rwnahhas/RMPH/">https://www.bookdown.org/rwnahhas/RMPH/</a>.

intro-MLEs.html

@@ -2082,7 +2082,7 @@
 </details><div class="cell-output-display">
 <div data-pagedtable="false">
   <script data-pagedtable-source="" type="application/json">
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+{"columns":[{"label":["mu-hat"],"name":[1],"type":["dbl"],"align":["right"]},{"label":["sigma-hat"],"name":[2],"type":["dbl"],"align":["right"]},{"label":["se_hat"],"name":[3],"type":["dbl"],"align":["right"]},{"label":["confint_left"],"name":[4],"type":["dbl"],"align":["right"]},{"label":["confint_right"],"name":[5],"type":["dbl"],"align":["right"]},{"label":["tstat"],"name":[6],"type":["dbl"],"align":["right"]},{"label":["pval"],"name":[7],"type":["dbl"],"align":["right"]},{"label":["confint covers true mu"],"name":[8],"type":["lgl"],"align":["right"]},{"label":["test rejects null hypothesis"],"name":[9],"type":["lgl"],"align":["right"]}],"data":[{"1":"97.68","2":"11.14","3":"1.114","4":"95.47","5":"99.89","6":"7.977","7":"2.691e-12","8":"TRUE","9":"TRUE"}],"options":{"columns":{"min":{},"max":[10]},"rows":{"min":[10],"max":[10]},"pages":{}}}
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 </div>
 </div>

intro-to-survival-analysis.html

@@ -433,7 +433,7 @@
     <div>
     <div class="quarto-title-meta-heading">Published</div>
     <div class="quarto-title-meta-contents">
-      <p class="date">Last modified: 2024-05-21: 13:20:45 (PM)</p>
+      <p class="date">Last modified: 2024-05-21: 13:48:43 (PM)</p>
     </div>
   </div>
 
@@ -522,7 +522,7 @@
 </div>
 </div>
 <div class="callout-body-container callout-body">
-<p>The term <em>Survival analysis</em> is a bit misleading. Survival outcomes can sometimes be analyzed using binomial models (logistic regression). <em>Time-to-event models</em> might be a better name.</p>
+<p>The term <em>survival analysis</em> is a bit misleading. Survival outcomes can sometimes be analyzed using binomial models (logistic regression). <em>Time-to-event models</em> or <em>survival time analysis</em> might be a better name.</p>
 </div>
 </div>
 </section></section><section id="time-to-event-outcome-distributions" class="level2" data-number="5.2"><h2 data-number="5.2" class="anchored" data-anchor-id="time-to-event-outcome-distributions">
@@ -2989,9 +2989,9 @@ <h3 class="anchored">Examples</h3>
 <span id="cb31-14"><a href="#cb31-14" aria-hidden="true" tabindex="-1"></a>    failure of a device or system.</span>
 <span id="cb31-15"><a href="#cb31-15" aria-hidden="true" tabindex="-1"></a><span class="ss">-   </span>insurance, particularly life insurance, where the</span>
 <span id="cb31-16"><a href="#cb31-16" aria-hidden="true" tabindex="-1"></a>    event is death.</span>
-<span id="cb31-17"><a href="#cb31-17" aria-hidden="true" tabindex="-1"></a>    </span>
+<span id="cb31-17"><a href="#cb31-17" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb31-18"><a href="#cb31-18" aria-hidden="true" tabindex="-1"></a>:::{.callout-note}</span>
-<span id="cb31-19"><a href="#cb31-19" aria-hidden="true" tabindex="-1"></a>The term *Survival analysis* is a bit misleading. Survival outcomes can sometimes be analyzed using binomial models (logistic regression). *Time-to-event models* might be a better name.</span>
+<span id="cb31-19"><a href="#cb31-19" aria-hidden="true" tabindex="-1"></a>The term *survival analysis* is a bit misleading. Survival outcomes can sometimes be analyzed using binomial models (logistic regression). *Time-to-event models* or *survival time analysis* might be a better name.</span>
 <span id="cb31-20"><a href="#cb31-20" aria-hidden="true" tabindex="-1"></a>:::</span>
 <span id="cb31-21"><a href="#cb31-21" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb31-22"><a href="#cb31-22" aria-hidden="true" tabindex="-1"></a><span class="fu">## Time-to-event outcome distributions</span></span>