<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>generalized linear models | Jesper N. Wulff</title><link>https://jespernwulff.github.io/tags/generalized-linear-models/</link><atom:link href="https://jespernwulff.github.io/tags/generalized-linear-models/index.xml" rel="self" type="application/rss+xml"/><description>generalized linear models</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Mon, 01 Jun 2026 00:00:00 +0200</lastBuildDate><image><url>https://jespernwulff.github.io/media/icon_hu_c98bc1085d22e9da.png</url><title>generalized linear models</title><link>https://jespernwulff.github.io/tags/generalized-linear-models/</link></image><item><title>ginteff</title><link>https://jespernwulff.github.io/software/ginteff/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://jespernwulff.github.io/software/ginteff/</guid><description>&lt;p&gt;&lt;code&gt;ginteff&lt;/code&gt; is an R port of the Stata &lt;a href="https://doi.org/10.1177/1536867X231175253" target="_blank" rel="noopener"&gt;ginteff&lt;/a&gt; command by Marius Radean (&lt;em&gt;The Stata Journal&lt;/em&gt;, 2023). It computes two- and three-way interaction effects — via partial derivatives or first differences — for fitted regression models, with delta-method standard errors.&lt;/p&gt;
&lt;p&gt;Built as a thin wrapper around &lt;a href="https://marginaleffects.com" target="_blank" rel="noopener"&gt;marginaleffects&lt;/a&gt;, it supports arbitrary variance–covariance specifications (&lt;code&gt;&amp;quot;HC3&amp;quot;&lt;/code&gt;, clustered, or a user-supplied sandwich matrix), which propagate through to the final interaction-effect standard errors.&lt;/p&gt;
&lt;pre&gt;&lt;code&gt;# install.packages(&amp;quot;remotes&amp;quot;)
remotes::install_github(&amp;quot;jespernwulff/ginteff&amp;quot;)
&lt;/code&gt;&lt;/pre&gt;</description></item><item><title>Binary Regression Models: An Average Partial Effects Approach</title><link>https://jespernwulff.github.io/publication/binary-regression-average-partial-effects/</link><pubDate>Mon, 01 Jun 2026 00:00:00 +0200</pubDate><guid>https://jespernwulff.github.io/publication/binary-regression-average-partial-effects/</guid><description/></item><item><title>Statistical Myths About Log-Transformed Dependent Variables and How to Better Estimate Exponential Models</title><link>https://jespernwulff.github.io/publication/log-transformed-dependent-variables/</link><pubDate>Thu, 01 Jul 2021 00:00:00 +0200</pubDate><guid>https://jespernwulff.github.io/publication/log-transformed-dependent-variables/</guid><description/></item><item><title>Interpreting Results From the Multinomial Logit Model: Demonstrated by Foreign Market Entry</title><link>https://jespernwulff.github.io/publication/multinomial-logit-foreign-entry/</link><pubDate>Wed, 01 Apr 2015 00:00:00 +0200</pubDate><guid>https://jespernwulff.github.io/publication/multinomial-logit-foreign-entry/</guid><description/></item></channel></rss>