Structural Equation Modeling - Continuation 2500-PL-PS-SP15-18

Structural equation modeling (SEM) is a powerful and still developing statistical technique that allows for addressing simple as well as complex research questions. While researchers are relatively familiar with the basic applications of SEM (e.g., Confirmatory Factor Analysis), their knowledge of more advanced models (e.g., SEM-based meta-analysis) is relatively limited. Consequently, potentially valuable insights have no chance to emerge and extend our knowledge of the world.

This course is a continuation of the introductory SEM course. Throughout the consecutive classes, participants will be presented with a range of advanced applications of SEM. We will discuss measurement invariance, multigroup analysis, SEM-based meta-analysis, latent variable interactions, power analysis for structural models, and methods of handling missing data. The classes will involve the combination of lectures and lab sessions focusing on the specification, estimation, and interpretation of structural equation models. All analyses will be performed in R lavaan and related packages.

Upon completing the course, students will be equipped for studying SEM independently in accordance with their professional needs.