Meta-analytic structural equation modeling (MASEM) is a method to systematically synthesize results from primary studies. The technique is increasingly popular in various research fields as it allows researchers to evaluate SEM models (e.g., path models and factor models) on meta-analytic correlations. 

With current MASEM methods, it is not evident how one can include group data, such as dichotomous variables indicating whether participants are in the experimental or control group, or dichotomized variables representing whether a person scored above or below some cut-off score on a continuous variable. In this PhD project, we develop and evaluate MASEM-methods that enable researchers to answer research questions involving group data. Specifically, we will focus on MASEM with biserial correlation coefficients, MASEM with Cohen’s d-to-r transformed point-biserial correlation coefficients, and on MASEM models for (latent) means.

This project is funded with the NWO Veni Fund awarded to Dr Suzanne Jak.