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.

Course outline

This two-day workshop provides:

  1. the basic concepts behind Structural Equation Modelling (SEM) and the assumptions involved,
  2. comparison of regression and path analysis,
  3. introduction of confirmatory factor analysis with measurement model for testing content validity and discriminant validity,
  4. 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.