Structural equation models (SEM) and multilevel models (MLM) offer vast flexibility for data analysis. With these techniques, researchers can work with observed and latent variables in dynamic ways to estimate direct, mediated/indirect, non-linear, and interaction effects. Using Mplus, these effects can be embedded in larger models of many types. In SEM, special cases with only observed variables include multiple regression and path analysis. With observed and latent variables a special case is confirmatory factor analysis (CFA).

In terms of MLM with clustered or nested data, such as students in classrooms or people in work teams, latent variables are used to model random intercepts and random slopes. This allows estimating relationships at multiple levels of analysis. Importantly, both SEM and MLM can be used to model longitudinal processes and effects, for example with latent growth modeling (LGM). Further, SEM and MLM are special cases of a more general modeling framework that can be called multilevel SEM, which allows SEM at multiple levels of analysis.

Conveniently, Mplus can estimate all of these with both traditional and Bayesian estimation methods, allowing researchers a wide variety of options for hypothesis testing. This 5-day workshop will provide an overview of various models and estimators in Mplus, including how to interpret results.

Course outcomes

At the conclusion of this course participants will have a working understanding of SEM, MLM, multilevel SEM, and LGM in Mplus. Real data and examples will be used throughout the course.

Participants will also learn how to use traditional and Bayesian methods of estimation and inference in Mplus. This will be accomplished by covering the following topics:

  1. Introducing Mplus: Mplus language, regression, covariation, and path analysis.
  2. Popular Regression Tools: Mediators, moderators, and instrumental variables.
  3. Working with Latent Variables: Confirmatory factor analysis structural equation modelling.
  4. Multilevel Modeling: Random intercepts, random slopes, multilevel path analysis, and multilevel SEM.
  5. Latent Growth Modeling: Longitudinal data and processes, with application in MLM and SEM.

Participants are encouraged to bring a laptop. All models will be estimated and interpreted during the course so a laptop is not necessary, but participants will find it very helpful to use the Mplus software.

view the Mplus demo

Course outline

Day 1 - Introducing Mplus

  • Regression, Covariation, and Statistical Models
  • Mplus and Parameter Estimation
  • Path Analysis
  • Model Fit and Model Selection

Day 2 - Path Analysis

  • Mediation
  • Instrumental Variable Methods
  • Moderation
  • Moderated Mediation and Mediated Moderation

Day 3 - SEM

  • Latent Variables
  • Confirmatory Factor Analysis
  • Structural Equation Modeling
  • Model Identification

Day 4 - MLM

  • Multilevel Data and Regression
  • Multilevel Path Analysis
  • Multilevel CFA and SEM
  • Random Slopes
Day 5 - LGM
  • Longitudinal Data and Processes
  • Latent Growth Models as Multilevel Models
  • Latent Growth Models as SEMs
  • Dynamic Latent Growth Modeling

Who should attend?

This course is targeted at researchers and PhD students from social, health, and physical sciences with a working knowledge of regression. A review of fundamental concepts before the Mplus course will greatly enhance uptake for those who are rusty with basic concepts such as variances, covariances, regression, and hypothesis testing. A brief introduction to these topics will be given at the start of the course, but there are many free online resources for studying them, including YouTube videos.

1st - 5th February 2016
Dr. Michael Zyphur

Location: Malaysia Theatre (MSD-B121), Melbourne School of Design


Registrations for the 2016 Mplus Course have now closed.  To register your interest in our 2017 Mplus Course, please email m-plus@unimelb.edu.au




The last Mplus course taught by Michael Zyphur was attended by 120 people from around the globe. Average participant ratings were 4.8/5 on a questionnaire assessing the overall quality of the course. Example comments are as follows:

This was an exceptional course - educational and entertaining on what is a difficult subject otherwise. Michael Zyphur should be commended for his energy and grasp of the material.

Really well organised. Mike is an excellent presenter - really animated and responsive to questions. He made a tough/dry subject fun and interesting. A great course.

Exactly what I needed for my research. Very engaging presenter.

Great coverage of different techniques. Topics covered are abundant. Great illustrations with examples. Quite a practical approach (not only theoretical) especially with the examples in Mplus. Lots of materials that can be reviewed post workshop for self-learning.

Loved the course. Mike was engaging and made the content easily accessible. Very pleased to have references provided for further learning and feel like I've gained a thorough base understanding of the material that can now be built on (with greater enthusiasm than I expected).