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<oembed><version>1.0</version><provider_name>Probably Overthinking It</provider_name><provider_url>https://www.allendowney.com/blog</provider_url><author_name>AllenDowney</author_name><author_url>https://www.allendowney.com/blog/author/allendowney_6dbrc4/</author_url><title>Resampling for Logistic Regression - Probably Overthinking It</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="jbWEixYNrA"&gt;&lt;a href="https://www.allendowney.com/blog/2023/01/20/resampling-for-logistic-regression/"&gt;Resampling for Logistic Regression&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://www.allendowney.com/blog/2023/01/20/resampling-for-logistic-regression/embed/#?secret=jbWEixYNrA" width="600" height="338" title="&#x201C;Resampling for Logistic Regression&#x201D; &#x2014; Probably Overthinking It" data-secret="jbWEixYNrA" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script type="text/javascript"&gt;
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</html><description>A recent question on Reddit asked about using resampling with logistic regression. The responses suggest two ways to do it, one parametric and one non-parametric. I implemented both of them and then invented a third, which is hybrid of the two. You can read the details of the implementation in the extended version of this article. Or you can click here to run the Jupyter notebook on Colab Different ways of computing sampling distributions &#x2013; and the statistics derived from... Read More Read More</description></oembed>
