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 [aut, cre], Maximilian Maier [aut], Eric-Jan Wagenmakers [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_4.0.0.zip, r-release: RoBMA_4.0.0.zip, r-oldrel: RoBMA_4.0.0.zip
macOS binaries:	r-release (arm64): RoBMA_3.6.1.tgz, r-oldrel (arm64): RoBMA_4.0.0.tgz, r-release (x86_64): RoBMA_4.0.0.tgz, r-oldrel (x86_64): RoBMA_4.0.0.tgz
Old sources:	RoBMA archive

Reverse dependencies:

Reverse suggests:

BayesTools, PublicationBiasBenchmark

Linking:

Please use the canonical form https://CRAN.R-project.org/package=RoBMA to link to this page.