Built site for gh-pages

.nojekyll

@@ -1 +1 @@
-27604cc5
+80d99a37

Linear-models-overview.html

@@ -3921,15 +3921,15 @@ <h3 class="anchored">Note</h3>
 <tbody>
 <tr class="odd">
 <td style="text-align: left;">full</td>
-<td style="text-align: right;">6.767</td>
+<td style="text-align: right;">7.118</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;">6.646</td>
+<td style="text-align: right;">6.437</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>
@@ -4065,11 +4065,11 @@ <h3 class="anchored">Note</h3>
 <div class="cell">
 <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) 34.30916</span></span>
-<span><span class="co">#&gt; age          .      </span></span>
-<span><span class="co">#&gt; weight      -0.08001</span></span>
-<span><span class="co">#&gt; protein      0.76405</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<span><span class="co">#&gt;                  s1</span></span>
+<span><span class="co">#&gt; (Intercept) 34.0221</span></span>
+<span><span class="co">#&gt; age          .     </span></span>
+<span><span class="co">#&gt; weight      -0.1145</span></span>
+<span><span class="co">#&gt; protein      1.0223</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">

index.html

@@ -389,7 +389,7 @@ <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: 2024-06-10: 16:47:49 (PM)</p>
+      <p class="date">Last modified: 2024-06-11: 12:19:39 (PM)</p>
     </div>
   </div>
 
@@ -511,6 +511,7 @@ <h2 class="unnumbered anchored" data-anchor-id="other-resources">Other resources
 <li><p><span class="citation" data-cites="kutoyants2023introduction">Kutoyants (<a href="references.html#ref-kutoyants2023introduction" role="doc-biblioref">2023</a>)</span> appears to be a complete book on Poisson models.</p></li>
 <li><p><span class="citation" data-cites="hardin2007generalized">Hardin and Hilbe (<a href="references.html#ref-hardin2007generalized" role="doc-biblioref">2018</a>)</span> uses Stata.</p></li>
 <li><p><span class="citation" data-cites="andrews2012data">Andrews and Herzberg (<a href="references.html#ref-andrews2012data" role="doc-biblioref">2012</a>)</span> is a classic “learn-by-example” book with many datasets amenable to GLMs</p></li>
+<li><p><span class="citation" data-cites="r4epi">Cannell and Livingston (<a href="references.html#ref-r4epi" role="doc-biblioref">2024</a>)</span> is another open-source, online textbook like this one; it is primarily about statistical programming, but it includes full chapters on <a href="https://www.r4epi.com/linear-regression">linear regression</a>, <a href="https://www.r4epi.com/linear-regression-1">logistic regression</a>, and <a href="https://www.r4epi.com/poisson-regression">Poisson regression</a>. There is currently (2024/06) a placeholder chapter for <a href="https://www.r4epi.com/cox-proportional-hazards-regression">survival analysis</a>.</p></li>
 </ul>
 </section>
 <section id="license" class="level2 unnumbered">
@@ -534,6 +535,9 @@ <h2 class="unnumbered anchored" data-anchor-id="license">License</h2>
 <div id="ref-andrews2012data" class="csl-entry" role="listitem">
 Andrews, David F, and Agnes M Herzberg. 2012. <em>Data: A Collection of Problems from Many Fields for the Student and Research Worker</em>. Springer Science &amp; Business Media. <a href="https://link.springer.com/book/10.1007/978-1-4612-5098-2">https://link.springer.com/book/10.1007/978-1-4612-5098-2</a>.
 </div>
+<div id="ref-r4epi" class="csl-entry" role="listitem">
+Cannell, Brad, and Melvin Livingston. 2024. <em>R for Epidemiology</em>. Online. <a href="https://www.r4epi.com/">https://www.r4epi.com/</a>.
+</div>
 <div id="ref-clayton2013statistical" class="csl-entry" role="listitem">
 Clayton, David, and Michael Hills. 2013. <em>Statistical Models in Epidemiology</em>. Oxford University Press. <a href="https://global.oup.com/academic/product/statistical-models-in-epidemiology-9780199671182">https://global.oup.com/academic/product/statistical-models-in-epidemiology-9780199671182</a>.
 </div>

intro-MLEs.html

@@ -2073,7 +2073,7 @@
 </details><div class="cell-output-display">
 <div data-pagedtable="false">
   <script data-pagedtable-source="" type="application/json">
-{"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":"98.05","2":"11.24","3":"1.124","4":"95.82","5":"100.3","6":"8.234","7":"7.556e-13","8":"TRUE","9":"TRUE"}],"options":{"columns":{"min":{},"max":[10]},"rows":{"min":[10],"max":[10]},"pages":{}}}
+{"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":"98.83","2":"9.87","3":"0.987","4":"96.88","5":"100.8","6":"10.17","7":"4.615e-17","8":"TRUE","9":"TRUE"}],"options":{"columns":{"min":{},"max":[10]},"rows":{"min":[10],"max":[10]},"pages":{}}}
   </script>
 </div>
 </div>