Package: remaCor 0.0.19

Gabriel Hoffman

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>.

Authors:Gabriel Hoffman [aut, cre]

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NEWS

# Install 'remaCor' in R:
install.packages('remaCor', repos = c('https://diseaseneurogenomics.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/diseaseneurogenomics/remacor/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

5.56 score 1 stars 4 packages 7 scripts 931 downloads 6 exports 39 dependencies

Last updated 9 months agofrom:63821de189. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 12 2024
R-4.5-win-x86_64OKNov 12 2024
R-4.5-linux-x86_64OKNov 12 2024
R-4.4-win-x86_64OKNov 12 2024
R-4.4-mac-x86_64OKNov 12 2024
R-4.4-mac-aarch64OKNov 12 2024
R-4.3-win-x86_64OKNov 12 2024
R-4.3-mac-x86_64OKNov 12 2024
R-4.3-mac-aarch64OKNov 12 2024

Exports:hotellingLSLS.empiricalplotCorplotForestRE2C

Dependencies:clicolorspaceEnvStatsfansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellmvtnormnlmenortestpillarpkgconfigplyrR6rbibutilsRColorBrewerRcppRcppArmadilloRdpackreshape2rlangscalesstringistringrtibbleutf8vctrsviridisLitewithr

Random effects meta-analysis for correlated test statistics

Rendered fromremaCor.Rmdusingknitr::rmarkdownon Nov 12 2024.

Last update: 2023-06-15
Started: 2020-02-25