Robust Bayesian Meta-Analyses
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Documentation for package ‘RoBMA’ version 4.0.0
Help Pages
A B C D E F G H I J K L M N P Q R S T U V W Z
| RoBMA-package | RoBMA: Robust Bayesian Meta-Analysis |
-- A --
| add_loo | Add LOO-PSIS to brma Objects |
| add_loo.brma | Add LOO-PSIS to brma Objects |
| add_marglik | Add Marginal Likelihood to brma Objects |
| add_marglik.brma | Add Marginal Likelihood to brma Objects |
| add_waic | Add WAIC to brma Objects |
| add_waic.brma | Add WAIC to brma Objects |
| 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. (2021) |
| as.matrix.brma_samples | Convert brma_samples to Matrix |
| as_draws | Convert brma Objects to posterior Draws Formats |
| as_draws.brma | Convert brma Objects to posterior Draws Formats |
| as_draws.brma_samples | Convert brma_samples to posterior Draws Formats |
| as_draws.default | Convert brma Objects to posterior Draws Formats |
| as_draws_array | Convert brma Objects to posterior Draws Formats |
| as_draws_array.brma | Convert brma Objects to posterior Draws Formats |
| as_draws_array.brma_samples | Convert brma_samples to posterior Draws Formats |
| as_draws_array.default | Convert brma Objects to posterior Draws Formats |
| as_draws_df | Convert brma Objects to posterior Draws Formats |
| as_draws_df.brma | Convert brma Objects to posterior Draws Formats |
| as_draws_df.brma_samples | Convert brma_samples to posterior Draws Formats |
| as_draws_df.default | Convert brma Objects to posterior Draws Formats |
| as_draws_list | Convert brma Objects to posterior Draws Formats |
| as_draws_list.brma | Convert brma Objects to posterior Draws Formats |
| as_draws_list.brma_samples | Convert brma_samples to posterior Draws Formats |
| as_draws_list.default | Convert brma Objects to posterior Draws Formats |
| as_draws_matrix | Convert brma Objects to posterior Draws Formats |
| as_draws_matrix.brma | Convert brma Objects to posterior Draws Formats |
| as_draws_matrix.brma_samples | Convert brma_samples to posterior Draws Formats |
| as_draws_matrix.default | Convert brma Objects to posterior Draws Formats |
| as_draws_rvars | Convert brma Objects to posterior Draws Formats |
| as_draws_rvars.brma | Convert brma Objects to posterior Draws Formats |
| as_draws_rvars.brma_samples | Convert brma_samples to posterior Draws Formats |
| as_draws_rvars.default | Convert brma Objects to posterior Draws Formats |
| as_zplot | Transform brma Object to Zplot |
| as_zplot.brma | Transform brma Object to Zplot |
-- B --
| bayes_factor.brma | Bayes Factor for brma Objects |
| Bem2011 | 9 experimental studies from Bem (2011) as described in Bem et al. (2011) |
| bf.brma | Bayes Factor for brma Objects |
| bias_prior_specification | Publication-bias prior specification |
| blup | Best Linear Unbiased Predictions (BLUPs) |
| blup.brma | Best Linear Unbiased Predictions for brma Objects |
| BMA | Bayesian Model-Averaged Meta-Analysis |
| BMA.glmm | Bayesian Model-Averaged Generalized Meta-Analysis |
| BMA.norm | Bayesian Model-Averaged Meta-Analysis |
| bPEESE | Bayesian Precision-Effect Estimate with Standard Errors (PEESE) Model |
| bPET | Bayesian Precision-Effect Test (PET) Model |
| bridge_sampler.brma | Bridge Sampling for brma Objects |
| brma | Bayesian Meta-Analysis |
| brma.glmm | Bayesian Generalized Meta-Analysis |
| brma.norm | Bayesian Meta-Analysis |
| bselmodel | Bayesian Selection Model |
-- C --
| check_loo | Check LOO Diagnostics for brma Objects |
| check_loo.brma | Check LOO Diagnostics for brma Objects |
| coef.brma | Extract Model Coefficients for brma Objects |
| contr.BayesTools | BayesTools Contrast Matrices |
| contr.independent | BayesTools Contrast Matrices |
| contr.meandif | BayesTools Contrast Matrices |
| contr.orthonormal | BayesTools Contrast Matrices |
| cooks.distance.brma | Cook's Distance for brma Objects |
| covratio | COVRATIO for brma Objects |
| covratio.brma | COVRATIO for brma Objects |
-- D --
| data_input | Input Data Specification |
| dfbetas.brma | DFBETAS for brma Objects |
| dffits | DFFITS for brma Objects |
| dffits.brma | DFFITS for brma Objects |
-- E --
| estimate_unit_information_sd | Estimate Unit Information Standard Deviation |
-- F --
| fitted.brma | Fitted Values for brma Objects |
| fitting_specification | Fitting specification |
| funnel | Funnel Plot for brma Object |
| funnel.brma | Funnel Plot for brma Object |
-- G --
| galbraith | Radial (Galbraith) Plot for brma Object |
| galbraith.brma | Radial (Galbraith) Plot for brma Object |
-- H --
| hatvalues.brma | Hat Values for brma Objects |
| Havrankova2025 | 1159 effect sizes from a meta-analysis of beauty and professional success by Havránková et al. (2025) |
| hist.zplot_brma | Histogram of Z-Statistics |
| Hoppen2025 | 37 studies from a meta-analysis of social comparison as a behavior change technique by Hoppen et al. (2025) |
-- I --
| influence.brma | Measure Influence for brma Objects |
| interpret | Interpret brma Results |
| interpret.brma | Interpret brma Results |
| interpret.default | Interpret brma Results |
-- J --
| Johnides2025 | 412 effect sizes from a meta-analysis of secondary benefits of family-based treatments by Johnides et al. (2025) |
-- K --
| Kroupova2021 | 881 estimates from 69 studies of a relationship between employment and educational outcomes collected by Kroupova et al. (2021) |
-- L --
| lines.zplot_brma | Add Zplot Density Lines |
| logLik.brma | Extract Log-Likelihood Matrix from brma Object |
| logml.brma | Log Marginal Likelihood for brma Objects |
| loo | LOO-PSIS for brma Objects |
| loo.brma | LOO-PSIS for brma Objects |
| loo_compare | Compare brma Models Using LOO |
| loo_compare.brma | Compare brma Models Using LOO |
| loo_compare.loo | Compare loo Objects Using LOO |
| loo_weights | Extract Normalized PSIS Weights from brma Object |
| loo_weights.brma | Extract Normalized PSIS Weights from brma Object |
| Lui2015 | 18 studies of a relationship between acculturation mismatch and intergenerational cultural conflict collected by Lui (2015) |
-- M --
| ManyLabs16 | 55 effect sizes from Many Labs 2 replication studies of Tversky and Kahneman (1981) framing effects |
| marginal_means | Estimated Marginal Means |
| marginal_means.brma | Estimated Marginal Means for brma Objects |
-- N --
| nobs.brma | Number of Observations for brma Objects |
-- P --
| plot.brma | Plots brma Object |
| plot.marginal_means.brma | Plot Estimated Marginal Means |
| plot.zplot_brma | Plot Zplot Results |
| plot_diagnostic | Plot MCMC Diagnostics |
| plot_diagnostic.brma | Plot MCMC Diagnostics |
| plot_diagnostic_autocorrelation | Plot MCMC Diagnostics |
| plot_diagnostic_autocorrelation.brma | Plot MCMC Diagnostics |
| plot_diagnostic_density | Plot MCMC Diagnostics |
| plot_diagnostic_density.brma | Plot MCMC Diagnostics |
| plot_diagnostic_trace | Plot MCMC Diagnostics |
| plot_diagnostic_trace.brma | Plot MCMC Diagnostics |
| plot_pet_peese | Plot PET-PEESE Fit of brma Object |
| plot_pet_peese.brma | Plot PET-PEESE Fit of brma Object |
| plot_prior | Plot Prior Distributions |
| plot_prior.brma | Plot Prior Distributions |
| plot_prior.prior | Plot Prior Distributions |
| plot_weightfunction | Plots Weight Function of brma Object |
| plot_weightfunction.brma | Plots Weight Function of brma Object |
| pooled_effect | Pooled Effect Size |
| pooled_effect.brma | Pooled Effect Size for brma Objects |
| pooled_heterogeneity | Pooled Heterogeneity |
| pooled_heterogeneity.brma | Pooled Heterogeneity for brma Objects |
| post_prob.brma | Posterior Model Probabilities for brma Objects |
| Poulsen2006 | 5 studies with a tactile outcome assessment from Poulsen et al. (2006) of the effect of potassium-containing toothpaste on dentine hypersensitivity |
| predict.brma | Predict From brma Object |
| print.brma | Summarize brma Object |
| print.brma_samples | Print brma_samples Object |
| print.interpret.brma | Interpret brma Results |
| print.marginal_means.brma | Print Estimated Marginal Means |
| print.RoBMA_data | Print method for RoBMA_data objects |
| print.summary.brma | Summarize brma Object |
| print.summary.brma_samples | Print summary.brma_samples Object |
| print.summary.marginal_means.brma | Print Summary of Estimated Marginal Means |
| print.summary.zplot_brma | Print Zplot Summary |
| print.summary_heterogeneity.brma | Print Summary of Heterogeneity |
| print.summary_models.RoBMA | Summarize Model-Averaged Component Weights |
| print.vif.brma | Print VIF Results |
| print_prior | Print Prior Distributions |
| print_prior.brma | Print Prior Distributions |
| print_prior.prior | Print Prior Distributions |
| prior | Prior Distribution |
| prior_factor | Factor Prior |
| prior_informed | Informed Prior |
| prior_none | Empty Prior |
| prior_PEESE | PEESE Prior |
| prior_PET | PET Prior |
| prior_specification | Prior specification |
| prior_weightfunction | Weightfunction Prior |
| publication_bias_prior_specification | Publication-bias prior specification |
-- Q --
| qqnorm.brma | Normal QQ Plot for brma Object |
-- R --
| radial | Radial (Galbraith) Plot for brma Object |
| radial.brma | Radial (Galbraith) Plot for brma Object |
| ranef | Random Effects |
| ranef.brma | Random Effects for brma Objects |
| regplot | Regression Plot (Bubble Plot) for brma Object |
| regplot.brma | Regression Plot (Bubble Plot) for brma Object |
| residuals.brma | Residuals for brma Objects |
| RoBMA | Robust Bayesian Model-Averaged Meta-Analysis |
| RoBMA.get_option | Options for the RoBMA package |
| RoBMA.options | Options for the RoBMA package |
| RoBMA.package | RoBMA: Robust Bayesian Meta-Analysis |
| RoBMA_control | Control MCMC fitting process |
| RoBMA_options | Options for the RoBMA package |
| RoBMA_package | RoBMA: Robust Bayesian Meta-Analysis |
| RoBMA_prior_specification | Prior specification for model-averaging |
| rstandard.brma | Internally Standardized Residuals for brma Objects |
| rstudent.brma | Externally Standardized (Studentized) Residuals for brma Objects |
-- S --
| set_autofit_control | Control MCMC fitting process |
| set_convergence_checks | Control MCMC fitting process |
| summary.brma | Summarize brma Object |
| summary.brma_samples | Summarize brma_samples Object |
| summary.marginal_means.brma | Summarize Estimated Marginal Means |
| summary.zplot_brma | Summarize Zplot Results |
| summary_heterogeneity | Summary of Heterogeneity |
| summary_heterogeneity.brma | Summary of Heterogeneity for brma Objects |
| summary_models | Summarize Model-Averaged Component Weights |
| summary_models.RoBMA | Summarize Model-Averaged Component Weights |
-- T --
| true_effects | True Effects |
| true_effects.brma | True Effects for brma Objects |
-- U --
| update.brma | Update a brma Fit |
-- V --
| vif | Variance Inflation Factors |
| vif.brma | Variance Inflation Factors for brma Objects |
-- W --
| waic | WAIC for brma Objects |
| waic.brma | WAIC for brma Objects |
| Wang2025 | 70 effect sizes from a meta-analysis of ChatGPT's impact on student learning by Wang and Fan (2025) |
| Weingarten2018 | 582 effect sizes examining the ease-of-retrieval effect from a meta-analysis by Weingarten and Hutchinson (2018) |
| wf_cumulative | Weightfunction Prior |
| wf_fixed | Weightfunction Prior |
| wf_independent | Weightfunction Prior |
-- Z --
| zplot | Plot Zplot Diagnostics Directly |
| zplot.brma | Plot Zplot Diagnostics Directly |
| zplot.zplot_brma | Plot Zplot Diagnostics Directly |