Introduction to Structural Equation Modelling with Mplus
A course covering the fundamental structural equation modelling (SEM) concepts through lectures and hands-on data analysis.
We last ran this course in February 2020. For any enquiries about this course or to express interest in it, please email firstname.lastname@example.org.
Professor Gordon Cheung
This course assumes that participants have a basic understanding of regression analysis. It does not assume prior experience with structural equation modelling or Mplus.
This two-day workshop provides:
- The basic concepts behind Structural Equation Modelling (SEM) and the assumptions involved,
- Comparison of regression and path analysis
- Introduction of confirmatory factor analysis with measurement model for testing content validity and discriminant validity
- Application of full structural model with latent variables. Hands-on data analysis with examples will be provided
At the conclusion of the workshop, participants will be able to:
- Understand the conceptual and statistical assumptions underlying SEM
- Write Mplus syntax for measurement model, path model and structural model with latent variables
- Interpret results in published articles that use SEM
This is part of a suite of workshops on using Mplus.
Cheung GW & Rensvold RB (2001). The effects of model parsimony and sampling error on the fit of structural equation models. Organizational Research Methods, 4: 235–263.
Hu L & Bentler PM (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1): 1–55.
Muthén LK & Muthén BO (1998–2015). Mplus User’s Guide (7th Edition). Los Angeles, CA: Muthén and Muthén.