Structural Equation Models



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Further and more detailed information, including the schedule, can be found in the current course tables in the syllabus of the respective course, if the course is offered in the next sessions. The following text serves as information on what can be expected in terms of content in the course.

Learning objectives: The course will provide a conceptual introduction to structural equation models, provide a thorough outline of model “fitting” and assessment, show participants: i) how to effectively program structural equation models using available software, ii) how to perform mediation and moderation analysis within the structural equation model framework, iii) how to extend basic models into multiple group situations, iv) and provide an introduction to models where common model assumptions regarding missing and non-normal data are not met. Course content: 1. Introduction to latent variable models, measurement error, path diagrams 2. Mediation models in the structural equation framework 3. Estimation, identification, interpretation of model parameters. 4. Scaling and interpretation issues 5. Scalar programming for structural equation models in R (lavaan). 6. Model fit and model improvement 7. General linear parameter constraints 8. Moderation analysis using 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. 12. Interactions 13. Longitudinal data (as time permits)