RoBMA: Robust Bayesian Meta-Analyses

A framework for Bayesian meta-analysis, including model estimation, prior specification, model comparison, prediction, summaries, visualizations, and diagnostics. The package fits single and model-averaged meta-analytic, meta-regression, multilevel, publication bias adjusted, and generalized linear mixed models The model-averaged meta-analytic models combine competing models based on their predictive performance, weight inference by posterior model probabilities, and test model components using Bayes factors (e.g., effect vs. no effect; Bartoš et al., 2022, <doi:10.1002/jrsm.1594>; Maier, Bartoš & Wagenmakers, 2022, <doi:10.1037/met0000405>; Bartoš et al., 2025, <doi:10.1037/met0000737>). Users can specify flexible prior distributions for effect sizes, heterogeneity, publication bias (including selection models and PET-PEESE), and moderators.

Version: 4.0.0
Depends: R (≥ 4.0.0)
Imports: BayesTools (≥ 0.3.0), bridgesampling, loo, MASS, parallel, runjags, rjags, stats, graphics, mvtnorm, scales, Rdpack, rlang, coda, ggplot2
LinkingTo: mvtnorm
Suggests: metafor, posterior, weightr, lme4, fixest, metaBMA, emmeans, metadat, testthat, vdiffr, knitr, rmarkdown, covr
Published: 2026-05-07
DOI: 10.32614/CRAN.package.RoBMA
Author: František Bartoš ORCID iD [aut, cre], Maximilian Maier ORCID iD [aut], Eric-Jan Wagenmakers ORCID iD [ths], Joris Goosen [ctb], Matthew Denwood [cph] (Original copyright holder of some modified code where indicated.), Martyn Plummer [cph] (Original copyright holder of some modified code where indicated.)
Maintainer: František Bartoš <f.bartos96 at gmail.com>
BugReports: https://github.com/FBartos/RoBMA/issues
License: GPL-3
URL: https://fbartos.github.io/RoBMA/
NeedsCompilation: yes
SystemRequirements: JAGS >= 4.3.1 (https://mcmc-jags.sourceforge.io/)
Citation: RoBMA citation info
Materials: README, NEWS
In views: Bayesian, MetaAnalysis
CRAN checks: RoBMA results

Documentation:

Reference manual: RoBMA.html , RoBMA.pdf
Vignettes: Introduction to RoBMA (source, R code)
Prior Distributions (source, R code)
Bayesian Meta-Analysis (source, R code)
Feature Coverage (source, R code)
Multilevel Meta-Analysis (source, R code)
Publication-Bias Adjustment (source, R code)
Location-Scale Meta-Analysis (source, R code)
Generalized Linear Mixed-Effects Meta-Analysis (source, R code)
Bayesian Model Averaging (source, R code)
Robust Bayesian Meta-Analysis (source, R code)
Tutorial: Adjusting for Publication Bias in JASP and R - Selection Models, PET-PEESE, and Robust Bayesian Meta-Analysis (source, R code)
Robust Bayesian Model-Averaged Meta-Regression (source, R code)
Multilevel Robust Bayesian Meta-Analysis (source, R code)
Multilevel Robust Bayesian Model-Averaged Meta-Regression (source, R code)
Informed Bayesian Model-Averaged Meta-Analysis in Medicine (source, R code)
Informed Bayesian Model-Averaged Meta-Analysis with Binary Outcomes (source, R code)
Zplot Publication-Bias Diagnostics (source, R code)

Downloads:

Package source: RoBMA_4.0.0.tar.gz
Windows binaries: r-devel: RoBMA_3.6.1.zip, r-release: RoBMA_3.6.1.zip, r-oldrel: RoBMA_3.6.1.zip
macOS binaries: r-release (arm64): RoBMA_3.6.1.tgz, r-oldrel (arm64): RoBMA_3.6.1.tgz, r-release (x86_64): RoBMA_3.6.1.tgz, r-oldrel (x86_64): RoBMA_3.6.1.tgz
Old sources: RoBMA archive

Reverse dependencies:

Reverse suggests: BayesTools, PublicationBiasBenchmark

Linking:

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