In between methods Developing and evaluating analysis approaches for individual participant data MASEM

Increasing access to individual participant data (IPD) offers opportunities to address new research questions through evidence synthesis. However, appropriate analytical methods are needed to realize this potential. This dissertation integrates individual participant data meta-analysis with meta-analytic structural equation modeling (MASEM), establishing a framework for IPD MASEM and providing methodological guidance and practical tools for applied researchers. It examines seven approaches for evaluating structural equation models using raw data from multiple studies, drawing on multilevel SEM, multigroup SEM, multivariate meta-analysis, and correlation-based MASEM. Empirical demonstrations and programming syntax illustrate how research questions and data characteristics inform method selection. A simulation study compares five approaches and shows that cluster-robust single-level SEM does not accurately recover within-study effects. It also performs worse than alternatives regarding exact model fit rejection rates and standard error bias. These findings support using alternatives such as partially saturated models and correlation-based One-Stage MASEM. To accommodate small numbers of primary studies, the dissertation extends parameter moderation to meta-analytic path modeling and provides an open-source programming tutorial. It also investigates combining IPD with aggregate data by generating synthetic raw data from correlation matrices and analyzing the resulting composite dataset. Together, these contributions clarify methodological choices and broaden the circumstances in which IPD MASEM can be conducted. A decision tree helps researchers select suitable approaches. Limitations include the focus on multivariate continuous normal data, frequentist methods, and simple structural models. Future work should extend these foundations, strengthen dissemination and adoption, and develop dedicated software to support IPD MASEM in applied research.