Package: RoBMA 4.0.0

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.

Authors:František Bartoš [aut, cre], Maximilian Maier [aut], Eric-Jan Wagenmakers [ths], Joris Goosen [ctb], Matthew Denwood [cph], Martyn Plummer [cph]

RoBMA_4.0.0.tar.gz
RoBMA_4.0.0.zip(r-4.7)RoBMA_4.0.0.zip(r-4.6)RoBMA_4.0.0.zip(r-4.5)
RoBMA_4.0.0.tgz(r-4.6-x86_64)RoBMA_4.0.0.tgz(r-4.6-arm64)RoBMA_4.0.0.tgz(r-4.5-x86_64)RoBMA_4.0.0.tgz(r-4.5-arm64)
RoBMA_4.0.0.tar.gz(r-4.7-arm64)RoBMA_4.0.0.tar.gz(r-4.7-x86_64)RoBMA_4.0.0.tar.gz(r-4.6-arm64)RoBMA_4.0.0.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
card.svg |card.png
RoBMA/json (API)
NEWS

# Install 'RoBMA' in R:

install.packages('RoBMA', repos = c('https://fbartos.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/fbartos/robma/issues

Pkgdown/docs site:https://fbartos.github.io

Uses libs:

jags– Just Another Gibbs Sampler for Bayesian MCMC - binary JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS was written with three aims in mind: * To have an engine for the BUGS language that runs on Unix * To be extensible, allowing users to write their own functions, distributions and samplers. * To be a plaftorm for experimentation with ideas in Bayesian modelling This package contains the 'jags' binary as well as the associated shared library modules loaded by the binary.
c++– GNU Standard C++ Library v3

Datasets:

Anderson2010 - 23 experimental studies from Anderson et al. (2010) that meet the best practice criteria
Andrews2021 - 39 study rows on household chaos and child executive functions from a meta-analysis by Andrews et al.
Bem2011 - 9 experimental studies from Bem
Havrankova2025 - 1159 effect sizes from a meta-analysis of beauty and professional success by Havránková et al.
Hoppen2025 - 37 studies from a meta-analysis of social comparison as a behavior change technique by Hoppen et al.
Johnides2025 - 412 effect sizes from a meta-analysis of secondary benefits of family-based treatments by Johnides et al.
Kroupova2021 - 881 estimates from 69 studies of a relationship between employment and educational outcomes collected by Kroupova et al.
Lui2015 - 18 studies of a relationship between acculturation mismatch and intergenerational cultural conflict collected by Lui
ManyLabs16 - 55 effect sizes from Many Labs 2 replication studies of Tversky and Kahneman (1981) framing effects
Poulsen2006 - 5 studies with a tactile outcome assessment from Poulsen et al. (2006) of the effect of potassium-containing toothpaste on dentine hypersensitivity
Wang2025 - 70 effect sizes from a meta-analysis of ChatGPT's impact on student learning by Wang and Fan
Weingarten2018 - 582 effect sizes examining the ease-of-retrieval effect from a meta-analysis by Weingarten and Hutchinson

On CRAN:

meta-analysis model-averaging publication-bias jags cpp

7.98 score 10 stars 71 scripts 604 downloads 1 mentions 73 exports 49 dependencies

Last updated from:09d07b90f9. Checks:12 OK, 1 FAIL. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	210
linux-devel-x86_64	OK	259
source / vignettes	OK	695
linux-release-arm64	OK	233
linux-release-x86_64	OK	261
macos-release-arm64	OK	191
macos-release-x86_64	OK	324
macos-oldrel-arm64	OK	151
macos-oldrel-x86_64	OK	378
windows-devel	OK	217
windows-release	OK	220
windows-oldrel	OK	199
wasm-release	FAIL	160

Exports:add_loo add_marglik add_waic as_draws as_draws_array as_draws_df as_draws_list as_draws_matrix as_draws_rvars as_zplot bayes_factor bf blup BMA BMA.glmm BMA.norm bPEESE bPET bridge_sampler brma brma.glmm brma.norm bselmodel check_loo contr.independent contr.meandif contr.orthonormal covratio dffits estimate_unit_information_sd funnel galbraith interpret logml loo loo_compare loo_weights marginal_means plot_diagnostic plot_diagnostic_autocorrelation plot_diagnostic_density plot_diagnostic_trace plot_pet_peese plot_prior plot_weightfunction pooled_effect pooled_heterogeneity post_prob print_prior prior prior_factor prior_informed prior_none prior_PEESE prior_PET prior_weightfunction radial ranef regplot RoBMA RoBMA.get_option RoBMA.options set_autofit_control set_convergence_checks summary_heterogeneity summary_models true_effects vif waic wf_cumulative wf_fixed wf_independent zplot

Dependencies:abind backports BayesTools bridgesampling Brobdingnag checkmate cli coda cpp11 distributional extraDistr farver generics ggplot2 glue gtable isoband labeling lattice lifecycle loo magrittr MASS Matrix matrixStats mvtnorm numDeriv pillar pkgconfig posterior R6 rbibutils RColorBrewer Rcpp RcppArmadillo Rdpack rjags rlang runjags S7 scales stringi stringr tensorA tibble utf8 vctrs viridisLite withr