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Computes the posterior model probabilities for standard meta-analysis models (null model vs. alternative model assuming either fixed- or random-effects, respectively). These posterior probabilities are used to estimate the overall mean effect size as the weighted average of the mean effect size estimates of the random- and fixed-effect model as proposed by Gronau, Van Erp, Heck, Cesario, Jonas, & Wagenmakers (2017, <doi:10.1080/23743603.2017.1326760>). The user can define a wide range of non-informative or informative priors for the mean effect size and the heterogeneity coefficient. Moreover, using pre-compiled Stan models, meta-analysis with continuous and discrete moderators with Jeffreys-Zellner-Siow (JZS) priors can be fitted and tested. This allows to compute Bayes factors and perform Bayesian model averaging across random- and fixed-effects meta-analysis with and without moderators.

copied from cf-staging / r-metabma
Type Size Name Uploaded Downloads Labels
conda 1.8 MB | osx-64/r-metabma-0.6.5-r36h7d45411_0.tar.bz2  4 years and 4 months ago 263 main
conda 1.9 MB | osx-64/r-metabma-0.6.5-r40h7d45411_0.tar.bz2  4 years and 4 months ago 273 main
conda 1.8 MB | linux-64/r-metabma-0.6.5-r40he524a50_0.tar.bz2  4 years and 4 months ago 2674 main
conda 1.8 MB | linux-64/r-metabma-0.6.5-r36he524a50_0.tar.bz2  4 years and 4 months ago 2730 main

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