remaCor: Random Effects Meta-Analysis for Correlated Test Statistics
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>.
| Version: |
0.0.9 |
| Depends: |
R (≥ 3.6.0), RUnit, clusterGeneration, ggplot2, grid, reshape2, methods |
| Imports: |
mvtnorm, compiler, Rdpack, stats |
| Suggests: |
knitr, metafor |
| Published: |
2022-09-07 |
| Author: |
Gabriel Hoffman [aut, cre] |
| Maintainer: |
Gabriel Hoffman <gabriel.hoffman at mssm.edu> |
| BugReports: |
https://github.com/GabrielHoffman/remaCor/issues |
| License: |
Artistic-2.0 |
| URL: |
https://github.com/GabrielHoffman/remaCor |
| NeedsCompilation: |
no |
| Citation: |
remaCor citation info |
| Materials: |
README NEWS |
| CRAN checks: |
remaCor results |
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