Structural Equation Models

About

1. Introduction to latent variable models, measurement error, path diagrams.
2. Estimation, identification, interpretation of model parameters.
3. Scaling and interpretation issues
4. Scalar programming for structural equation models in R-lavaan and STATA.
5. Mediation models in the structural equation framework.
6. Model fit and model improvement
7. General linear parameter constraints
8. Multiple-group models
9. Introduction to models for means and intercepts
10. The FIML approach to analysis with missing data
11. Alternative estimators for non-normal data.

Course leader

Andreas Hermann & Douglas Baer

Target group

Master | PhD | Postdoc | Professional

Fee info