Meta-Analytic Selection Models for Dependent Effect Sizes

Fits a flexible class of p-value selection models for meta-analysis and meta-regression models, providing standard errors and confidence intervals based on either cluster-robust variance estimators (i.e., sandwich estimators) or cluster-level bootstrapping to handle dependent effect size estimates, as described in Pustejovsky, Citkowicz, and Joshi (2025) and Citkowicz, Pustejovsky, and Joshi (2026) . Supported models include generalizations of the step-function selection model as proposed by Vevea and Hedges (1995) and the beta-function selection model as proposed by Citkowicz and Vevea (2017) .