About Anaconda Help Download Anaconda

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
Click on a badge to see how to embed it in your web page
badge
https://anaconda.org/conda-forge/r-metabma/badges/version.svg
badge
https://anaconda.org/conda-forge/r-metabma/badges/latest_release_date.svg
badge
https://anaconda.org/conda-forge/r-metabma/badges/latest_release_relative_date.svg
badge
https://anaconda.org/conda-forge/r-metabma/badges/platforms.svg
badge
https://anaconda.org/conda-forge/r-metabma/badges/license.svg
badge
https://anaconda.org/conda-forge/r-metabma/badges/downloads.svg

© 2024 Anaconda, Inc. All Rights Reserved. (v4.0.6) Legal | Privacy Policy