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Structural Equation Modeling

The purpose of this course is to introduce research master students to a general statistical framework that brings together multiple regression and factor analysis: the Structural Equation Modeling (SEM) framework. Until now, research master students have been trained in estimating multiple regression models and factor analysis models separately. However, it is possible to estimate such modeling elements (a structural and measurement part) simultaneously within one model, and evaluate the fit ofsuch a model to the data.Mastering this statistical approach will (1) allow students to tackle new exciting research questions in their disciplines and (2) allow them to understand substantive research papers in the social and behavioural sciences or methodological research papers in which SEM is applied or further developed.In the first four weeks of the course, we introduce students to the basic concepts of SEM. In the remaining three weeks, we consider the logic, estimation, and interpretation of more advanced SEM or related (multilevel regression)models that are particularly useful for the analysis of longitudinal data.