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remaCor  

Random Effects Meta-Analysis for Correlated Test Statistics
View on CRAN: Click here


Download and install remaCor package within the R console
Install from CRAN:
install.packages("remaCor")

Install from Github:
library("remotes")
install_github("cran/remaCor")

Install by package version:
library("remotes")
install_version("remaCor", "0.0.18")



Attach the package and use:
library("remaCor")
Maintained by
Gabriel Hoffman
[Scholar Profile | Author Map]
First Published: 2022-09-07
Latest Update: 2023-06-21
Description:
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. .
How to cite:
Gabriel Hoffman (2022). remaCor: Random Effects Meta-Analysis for Correlated Test Statistics. R package version 0.0.18, https://cran.r-project.org/web/packages/remaCor. Accessed 27 Mar. 2025.
Previous versions and publish date:
0.0.9 (2022-09-07 10:30), 0.0.11 (2022-11-10 20:10), 0.0.16 (2023-06-21 15:00)
Other packages that cited remaCor R package
View remaCor citation profile
Other R packages that remaCor depends, imports, suggests or enhances
Complete documentation for remaCor
Functions, R codes and Examples using the remaCor R package
Some associated functions: LS.empirical . LS . RE2C . hotelling . pkg.env . plotCor . plotForest . 
Some associated R codes: LS.R . LS_empirical_pvalue.R . RE2C.R . RcppExports.R . hotelling.R . other_implied_functions.R . plots.R .  Full remaCor package functions and examples
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