A framework for estimating ensembles of meta-analytic models
(assuming either presence or absence of the effect, heterogeneity, and
publication bias) and using Bayesian model averaging to combine them. The
ensembles use Bayes factors to test for the presence or absence of the
individual components (e.g., effect vs. no effect) and model-averages
parameter estimates based on posterior model probabilities
(Maier, Bartoš & Wagenmakers, 2020,