A framework for estimating ensembles of meta-analytic, meta-regression, and multilevel models (assuming either presence or absence of the effect, heterogeneity, publication bias, and moderators). The RoBMA framework uses Bayesian model-averaging to combine the competing meta-analytic models into a model ensemble, weights the posterior parameter distributions based on posterior model probabilities and uses Bayes factors to test for the presence or absence of the individual components (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 define a wide range of prior distributions for the effect size, heterogeneity, publication bias (including selection models and PET-PEESE), and moderator components. The package provides convenient functions for summary, visualizations, and fit diagnostics.
Version: 3.5.0 Depends: R (≥ 4.0.0) Imports: BayesTools (≥ 0.2.19), runjags, rjags, stats, graphics, mvtnorm, scales, Rdpack, rlang, coda, ggplot2 LinkingTo: mvtnorm Suggests: parallel, metaBMA, metafor, weightr, lme4, fixest, emmeans, metadat, testthat, vdiffr, knitr, rmarkdown, covr Published: 2025-06-11 DOI: 10.32614/CRAN.package.RoBMA Author: FrantiÅ¡ek BartoÅ¡ [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: FrantiÅ¡ek BartoÅ¡ <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.pdf Vignettes: Fitting Custom Meta-Analytic Ensembles (source, R code)Please use the canonical form https://CRAN.R-project.org/package=RoBMA to link to this page.
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