metaselection: 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 clusterrobust variance estimators (i.e., sandwich estimators) or clusterlevel 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 stepfunction selection model as proposed by Vevea and Hedges (1995) and the betafunction selection model as proposed by Citkowicz and Vevea (2017) .