| RoBMA-package {RoBMA} | R Documentation |
RoBMA: Robust Bayesian meta-analysis
Description
RoBMA: Bayesian model-averaged meta-analysis with adjustments for publication bias and ability to specify informed prior distributions and draw inference with inclusion Bayes factors.
User guide
See Bartoš et al. (2022), Maier et al. (2022), and Bartoš et al. (2022) for details regarding the RoBMA methodology.
More details regarding customization of the model ensembles are provided in the Reproducing BMA, BMA in Medicine, and Fitting Custom Meta-Analytic Ensembles vignettes. Please, use the "Issues" section in the GitHub repository to ask any further questions.
Author(s)
František Bartoš f.bartos96@gmail.com
References
Bartoš F, Maier M, Quintana DS, Wagenmakers E (2022).
“Adjusting for publication bias in JASP and R — Selection models, PET-PEESE, and robust Bayesian meta-analysis.”
Advances in Methods and Practices in Psychological Science, 5(3), 1–19.
doi:10.1177/25152459221109259.
Bartoš F, Maier M, Wagenmakers E, Doucouliagos H, Stanley TD (2022).
“Robust Bayesian meta-analysis: Model-averaging across complementary publication bias adjustment methods.”
Research Synthesis Methods.
doi:10.1002/jrsm.1594.
Maier M, Bartoš F, Wagenmakers E (2022).
“Robust Bayesian Meta-Analysis: Addressing Publication Bias with Model-Averaging.”
Psychological Methods.
doi:10.1037/met0000405.
See Also
Useful links: