Structural equation models and multilevel models offer vast flexibility for data analysis. With these techniques, researchers can work with observed and latent variables to estimate a wide variety of effects. Using Mplus, these effects can be embedded in larger models of many types. In terms of structural equation modeling, special cases with only observed variables include multiple regression and path analysis. With observed and latent variables, special cases include confirmatory factor analysis and latent growth models.
In terms of multilevel modeling with clustered or nested data, such as students in classrooms or people in work teams, latent variables are used to model group averages and differences in effects across groups (i.e., random intercepts and random slopes, respectively). This allows estimating relationships at multiple levels of analysis. Multilevel models can also be used to examine longitudinal processes and effects, including latent growth modeling as a special case. Furthermore, both structural equation and multilevel models can be understood as special cases of a more general modeling framework that can be called multilevel structural equation modeling, which estimates structural equations at multiple levels of analysis.
Conveniently, Mplus can estimate all of these with both traditional and Bayes estimators, allowing researchers a wide variety of options for hypothesis testing. This 5-day workshop will provide an overview of these models in Mplus, including how to interpret results.
At the conclusion of this course participants will have a working understanding of structural equation modeling and multilevel modeling in Mplus. Real data and examples will be used throughout the course. Participants will also learn how to use traditional and Bayes estimators. This will be accomplished by covering the following topics:
- Introducing Mplus: Mplus language, regression, covariation, and path analysis.
- Popular Regression Tools: Mediators, moderators, and instrumental variables.
- Working with Latent Variables: Confirmatory factor analysis and structural equation modelling.
- Multilevel Modeling: Random intercepts, random slopes, multilevel path analysis, and multilevel structural equation modeling.
- Latent Growth Modeling: Longitudinal data and processes, applied using multilevel and structural equation modeling.
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.
Day 1 - Introducing Mplus
- Regression, Covariation, and Statistical Models
- Mplus and Parameter Estimation
- Path Analysis
- Model Fit and Model Selection
Day 2 - Path Analysis
- Instrumental Variable Methods
- Moderated Mediation
Day 3 - SEM
- Latent Variables
- Confirmatory Factor Analysis
- Structural Equation Modeling
- Model Identification
Day 4 - MLM
- Multilevel Data and Regression
- Multilevel Path Analysis
- Multilevel Confirmatory Factor Analysis and Structural Equation Modeling
- Random Slopes
- Longitudinal Data and Processes
- Latent Growth Models as Multilevel Models
- Latent Growth Models as Structural Equation Models
- 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.
5th - 9th February 2018
Dr. Michael Zyphur
Location: The University of Melbourne, Parkville, Victoria, Australia
Registrations for the 2018 Mplus Course are now closed.
If you have registration queries, please email email@example.com
The last Mplus course taught by Michael Zyphur was attended by roughly 100 people from around the globe. Average participant ratings were 4.8/5 on a questionnaire assessing the overall quality of the course. Example comments from participants 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).