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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 1.5 MB | win-64/r-metabma-0.6.9-r43h8ae3a7c_0.conda  5 months and 20 days ago 261 main
conda 1.5 MB | win-64/r-metabma-0.6.9-r44h8ae3a7c_0.conda  5 months and 20 days ago 254 main
conda 1.5 MB | osx-64/r-metabma-0.6.9-r43hc83a2cd_0.conda  5 months and 20 days ago 224 main
conda 1.5 MB | osx-64/r-metabma-0.6.9-r44hc83a2cd_0.conda  5 months and 20 days ago 205 main
conda 1.7 MB | linux-64/r-metabma-0.6.9-r43h93ab643_0.conda  5 months and 20 days ago 686 main
conda 1.7 MB | linux-64/r-metabma-0.6.9-r44h93ab643_0.conda  5 months and 20 days ago 652 main

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