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Hypothesis Tests Under Separation
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.
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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