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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), and random effects meta-analysis uses the method of Han, et al. 2016.
# Run fixed effects meta-analysis, accounting for correlation
LS( beta, stders, Sigma)
# Run random effects meta-analysis, accounting for correlation
RE2C( beta, stders, Sigma)devtools::install_github("DiseaseNeurogenomics/remaCor")These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.