A conditional posterior based on a variance-weighted projection yields asymptotically valid frequentist credible intervals for a binary treatment effect in high-dimensional logistic regression.
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Valid Bayesian Inference based on Variance Weighted Projection for High-Dimensional Logistic Regression with Binary Covariates
A conditional posterior based on a variance-weighted projection yields asymptotically valid frequentist credible intervals for a binary treatment effect in high-dimensional logistic regression.