Introduction to Structural Equation Modelling with Mplus
A course covering the fundamental structural equation modelling (SEM) concepts through lectures and hands-on data analysis.
For any concerns regarding this course, please email email@example.com.
Wednesday 19 – Thursday 20 February 2020
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 have simplified our fee structure to make it easier to show up front. We no longer have an earlybird period, and the fees for this course are simply:
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.