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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>.
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Package details |
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| Author | Gabriel Hoffman [aut, cre] (<https://orcid.org/0000-0002-0957-0224>) |
| Maintainer | Gabriel Hoffman <gabriel.hoffman@mssm.edu> |
| License | Artistic-2.0 |
| Version | 0.0.18 |
| URL | https://diseaseneurogenomics.github.io/remaCor/ |
| Package repository | View on CRAN |
| Installation |
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