• Promovendus: Lennert Groot
• Promotors: Frans Oort, Suzanne Jak, Kees Jan Kan

In this project we will extend the scope of research questions that can be answered with meta-analytical structural equation modeling (MASEM), and enable researchers to utilize the full potential of all available data. Consequently, policy makers can base decisions on high quality reviews that include all relevant evidence. In particular, I will investigate the possibilities of synthesizing raw datasets, instead of summary statistics, when conducting MASEM. 

This project is funded through an NWO-Vidi grant entitled 'No Data Left Behind' awarded to dr. Suzanne Jak. and runs from 2022 – 2026.

• Promovendus: Hannelies de Jonge
• Promotors: Suzanne Jak, Kees Jan Kan, Frans Oort

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.