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Date created: 2023-04-10 02:56 PM | Last Updated: 2023-07-31 05:07 PM

Identifier: DOI 10.17605/OSF.IO/WN2S4

Category: Project

Description: Separation commonly occurs in political science, usually when a binary ex- planatory variable perfectly predicts a binary outcome. In these situations, methodologists often recommend penalized maximum likelihood or Bayesian estimation. But researchers might struggle to identify an appropriate penalty or prior distribution. Fortunately, I show that researchers can easily test hy- potheses about the model coefficients with standard frequentist tools. While the popular Wald test produces misleading (even nonsensical) p-values under separation, I show that likelihood ratio tests and score tests behave in the usual manner. Therefore, researchers can produce meaningful p-values with standard frequentist tools under separation without the use of penalties or prior information.

License: CC-By Attribution 4.0 International

Has supplemental materials for Hypothesis Tests Under Separation on SocArXiv

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Hypothesis Tests Under Separation

This OSF project houses several documents that support my 2023 Politial Analysis paper titled "Hypothesis Tests Under Separation."

Pre-Print: You can find the pre-print here.

Reproduction Archive: You can find a compressed reproduction archive here. Also on Dataverse at https://doi.org/10.7910/DVN/6EYRJG

Computational Companion: You can find the computational arch…

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