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    <title>ChatGPT on ouR data generation</title>
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    <managingEditor>keith.goldfeld@nyumc.org (Keith Goldfeld)</managingEditor>
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      <title>Can ChatGPT help construct non-trivial statistical models? An example with Bayesian &#34;random&#34; splines</title>
      <link>https://www.rdatagen.net/post/2024-10-08-can-chatgpt-help-construct-non-trivial-bayesian-models-with-cluster-specific-splines/</link>
      <pubDate>Tue, 08 Oct 2024 00:00:00 +0000</pubDate><author>keith.goldfeld@nyumc.org (Keith Goldfeld)</author>
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      <description>&lt;p&gt;I’ve been curious to see how helpful ChatGPT can be for implementing relatively complicated models in &lt;code&gt;R&lt;/code&gt;. About two years ago, I &lt;a href=&#34;https://www.rdatagen.net/post/2022-11-01-modeling-secular-trend-in-crt-using-gam/&#34; target=&#34;_blank&#34;&gt;described&lt;/a&gt; a model for estimating a treatment effect in a cluster-randomized stepped wedge trial. We used a generalized additive model (GAM) with site-specific splines to account for general time trends, implemented using the &lt;code&gt;mgcv&lt;/code&gt; package. I’ve been interested in exploring a Bayesian version of this model, but hadn’t found the time to try - until I happened to pose this simple question to ChatGPT:&lt;/p&gt;</description>
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