Package: RobustBayesianCopas 2.0

Ray Bai

RobustBayesianCopas: Robust Bayesian Copas Selection Model

Fits the robust Bayesian Copas (RBC) selection model of Bai et al. (2020) <arxiv:2005.02930> for correcting and quantifying publication bias in univariate meta-analysis. Also fits standard random effects meta-analysis and the Copas-like selection model of Ning et al. (2017) <doi:10.1093/biostatistics/kxx004>.

Authors:Ray Bai

RobustBayesianCopas_2.0.tar.gz
RobustBayesianCopas_2.0.tar.gz(r-4.5-noble)RobustBayesianCopas_2.0.tar.gz(r-4.4-noble)
RobustBayesianCopas_2.0.tgz(r-4.4-emscripten)RobustBayesianCopas_2.0.tgz(r-4.3-emscripten)
RobustBayesianCopas.pdf |RobustBayesianCopas.html✨
RobustBayesianCopas/json (API)

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

Peer review:

Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3
Datasets:
  • Barlow2014 - A Meta-Analysis on the Effect of Parent Training Programs vs. Control for Improving Parental Psychosocial Health Within 4 Weeks After Intervention
  • Hackshaw1997 - A Meta-Analysis on the Relationship Between Second-hand Tobacco Smoke and Lung Cancer
  • antidepressants - A Meta-Analysis on the Efficacy of Antidepressants

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

jagscpp

1.00 score 224 downloads 5 exports 7 dependencies

Last updated 4 years agofrom:61efe22f8c. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 01 2024
R-4.5-linuxOKDec 01 2024

Exports:BayesNonBiasCorrectedCopasLikeSelectionD.measureRobustBayesianCopasStandardMetaAnalysis

Dependencies:clueclustercodalatticerjagsrpartstatip