The course will provide a conceptual introduction to structural equation models, provide a thorough outline of model “fitting” and assessment, teach how to effectively program structural equation models using available software, demonstrate how to extend basic models into multiple group situations, and provide an introduction to models where common model assumptions regarding missing and non-normal data are not met.
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.