Random Effects Meta-Analysis for Correlated Test Statistics R package remaCor version 0.0.20 CRAN Task View: MetaAnalysis (https://CRAN.R-project.org/view=MetaAnalysis) Meta-analysis is widely used to summarize estimated effects sizes across multiple statistical tests. Standard fixed and random effect meta-analysis methods assume that the estimated of the effect sizes are statistically independent. Here we relax this assumption and enable meta-analysis when the correlation matrix between effect size estimates is known. Fixed effect meta-analysis uses the method of Lin and Sullivan (2009) <doi:10.1016/j.ajhg.2009.11.001>, and random effects meta-analysis uses the method of Han, et al. <doi:10.1093/hmg/ddw049>. Software Depends: R (>= 3.6.0), ggplot2, methods Imports: mvtnorm, grid, reshape2, compiler, Rcpp, EnvStats, Rdpack, stats LinkingTo: Rcpp, RcppArmadillo Suggests: knitr, RUnit, clusterGeneration, metafor Gabriel Hoffman <gabriel.hoffman@mssm.edu> Comprehensive R Archive Network (CRAN) Gabriel Hoffman [aut, cre] (ORCID: <https://orcid.org/0000-0002-0957-0224>) Artistic-2.0 2025-08-20 application/tgz https://CRAN.R-project.org/package=remaCor doi:10.32614/CRAN.package.remaCor