Introduction to Structural Equation Modelling with Mplus
This course by Professor Gordon Cheung covers basic structural equation modelling (SEM) concepts and hands-on data analysis.
Wednesday 20 – Thursday 21 February 2019
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; we are only offering the more advanced courses in Auckland at this point.
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.