CRAN/E | remaCor

remaCor

Random Effects Meta-Analysis for Correlated Test Statistics

Installation

About

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.

Citation remaCor citation info
diseaseneurogenomics.github.io/remaCor/
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Version 0.0.18
R ≥ 3.6.0
Published 2024-02-08 81 days ago
Needs compilation? yes
License Artistic-2.0
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Maintainer

Maintainer

Gabriel Hoffman

gabriel.hoffman@mssm.edu

Authors

Gabriel Hoffman

aut / cre

Material

README
NEWS
Reference manual
Package source

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MetaAnalysis

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remaCor: Random effects meta-analysis for correlated test statistics

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

remaCor archive

Depends

R ≥ 3.6.0
ggplot2
methods

Imports

mvtnorm
grid
reshape2
compiler
Rcpp
EnvStats
Rdpack
stats

Suggests

knitr
RUnit
clusterGeneration
metafor

LinkingTo

Rcpp
RcppArmadillo

Reverse Imports

variancePartition