The present study took a meta-analytic approach to investigate whether students' engagement acts as a mediator in the association between affective teacher-student relationships and students' achievement. Furthermore, we examined whether results differed for primary and secondary school and whether similar results were found in a longitudinal subsample. Our sample consisted of 189 studies (249,198 students in total) that included students from preschool to high school. A distinction was made between positive relationship aspects (e.g., closeness) and negative relationship aspects (e.g., conflict). Meta-analytic structural equation modeling showed that, overall, the associations between both positive relationships and achievement and negative relationships and achievement were partially mediated by student engagement. Subsequent analyses revealed that mediation is applicable to both primary and secondary school. Only the direct association between positive relationships and engagement was stronger in secondary school than in primary school. Finally, partial mediation was also found in the longitudinal subsample.

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Meta-analytic structural equation modeling (MASEM) is an increasingly popular metaanalytic technique that combines the strengths of meta-analysis and structural equation modeling. MASEM facilitates the evaluation of complete theoretical models (e.g., path models or factor analytic models), accounts for sampling covariance between effect sizes, and provides measures of overall fit of the hypothesized model on meta-analytic data. We propose a novel MASEM method, One-Stage MASEM, which is better suitable to explain study-level heterogeneity than existing methods. One-Stage MASEM allows researchers to incorporate continuous or categorical moderators into the MASEM, in which any parameter in the structural equation model (e.g., path coefficients and factor loadings) can be modeled by the moderator variable, while the method does not require complete data for the primary studies included in the meta-analysis. We illustrate the new method on two real datasets, evaluate its empirical performance via a computer simulation study, and provide user-friendly R-functions and annotated syntax to assist researchers in applying One-Stage MASEM. We close the paper by presenting several future research directions.

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