Bayesian MASEM is a newly developed meta-analytic technique for synthesizing SEM results from multiple studies. The method can handle missing correlations appropriately (it works even if the primary studies only contain one correlation), as well as perform model fit assessment. In addition, the method allows between-studies heterogeneity in SEM parameters. Continuous and/or categorical moderators such as study-specific charateristics can be included to explain the between-studies heterogeneity in SEM parameters.
Four examples are provided illustrating how to use the Bayesian MASEM approach. Two are mediation models and two are CFA models.