RoBMA

Description

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.

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  installed size is  6.3Mb
  sub-directories of 1Mb or more:
    doc    3.1Mb
    libs   1.7Mb

  installed size is  6.4Mb
  sub-directories of 1Mb or more:
    doc    3.1Mb
    libs   1.7Mb

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  installed size is  6.3Mb
  sub-directories of 1Mb or more:
    doc    3.1Mb
    libs   1.7Mb

  installed size is  6.4Mb
  sub-directories of 1Mb or more:
    doc    3.1Mb
    libs   1.7Mb

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