Structural Equation Modeling with Categorical Data - Online Course
A 4-Day Livestream Seminar Taught by
Sonja WinterTuesday, July 7 —
Friday, July 10, 2026
10:30am-12:30pm (convert to your local time)
1:30pm-3:00pm
Structural equation modeling (SEM) is a framework for fitting many types of statistical models, including simple regression models, multivariate path models, confirmatory factor models, latent variable path models, and latent growth models. Since its inception, the standard SEM has been a linear model with normally distributed outcomes. This has been a big limitation because many outcome variables are binary or ordinal in almost every discipline.
While many SEM packages are still limited to linear/normal models, the last decade has seen the emergence of several SEM packages that do an excellent job of estimating non-normal models. Unfortunately, these models differ in several ways from standard SEM, and there is little didactic literature on how to properly use and interpret categorical SEM.
This seminar fills that gap by presenting a comprehensive treatment of SEM for binary and ordinal outcomes, using two of the best software packages for the task: Mplus and lavaan (a package for R).
Starting July 7, this seminar will be presented as a 4-day synchronous, livestream workshop via Zoom. Each day will feature two lecture sessions with hands-on exercises, separated by a 1-hour break. Live attendance is recommended for the best experience. But if you can’t join in real time, recordings will be available within 24 hours and can be accessed for four weeks after the seminar.
Closed captioning is available for all live and recorded sessions. Captions can be translated to a variety of languages including Spanish, Korean, and Italian. For more information, click here.
ECTS Equivalent Points: 1
More details about the course content
This 4-day online seminar provides a comprehensive, hands-on introduction to structural equation modeling with binary and ordinal outcomes. Topics include foundational differences between linear/normal SEM and categorical SEM; logistic and probit regression; path models with binary mediators and outcomes; confirmatory factor analysis and full SEM with binary and ordinal indicators; and advanced applications such as multiple-group CFA, measurement invariance testing, and missing data handling for categorical variables.
Throughout, you will work with empirical examples in both Mplus and R (lavaan), with explicit attention to syntax, estimation choices, and interpretation.
By the end of the course, you’ll be able to specify, estimate, and interpret path models, CFAs, and SEMs for binary and ordinal data; choose appropriate link functions and estimators; diagnose and address common pitfalls unique to categorical SEM; conduct measurement invariance tests with categorical indicators; and confidently implement these models in Mplus and, where supported, R.
This 4-day online seminar provides a comprehensive, hands-on introduction to structural equation modeling with binary and ordinal outcomes. Topics include foundational differences between linear/normal SEM and categorical SEM; logistic and probit regression; path models with binary mediators and outcomes; confirmatory factor analysis and full SEM with binary and ordinal indicators; and advanced applications such as multiple-group CFA, measurement invariance testing, and missing data handling for categorical variables.
Throughout, you will work with empirical examples in both Mplus and R (lavaan), with explicit attention to syntax, estimation choices, and interpretation.
By the end of the course, you’ll be able to specify, estimate, and interpret path models, CFAs, and SEMs for binary and ordinal data; choose appropriate link functions and estimators; diagnose and address common pitfalls unique to categorical SEM; conduct measurement invariance tests with categorical indicators; and confidently implement these models in Mplus and, where supported, R.
Computing
Empirical examples and exercises will be demonstrated using Mplus and R. To participate in the hands-on exercises, you should have a computer with Mplus and/or R installed.
All analyses can be completed using Mplus, while many (but not all) can be completed using R. R users should also install RStudio, a freely available interface, and the lavaan package for SEM.
The demo version of Mplus will suffice.
You should have good familiarity with the use of Mplus or R, including opening and executing data files and programs.
If you’d like to familiarize yourself with Mplus basics before the seminar begins, we recommend reading through UCLA’s short guide here.
If you’d like to use R for this course but don’t yet have much experience with that package, here are some excellent online resources for building your R skills.
Empirical examples and exercises will be demonstrated using Mplus and R. To participate in the hands-on exercises, you should have a computer with Mplus and/or R installed.
All analyses can be completed using Mplus, while many (but not all) can be completed using R. R users should also install RStudio, a freely available interface, and the lavaan package for SEM.
The demo version of Mplus will suffice.
You should have good familiarity with the use of Mplus or R, including opening and executing data files and programs.
If you’d like to familiarize yourself with Mplus basics before the seminar begins, we recommend reading through UCLA’s short guide here.
If you’d like to use R for this course but don’t yet have much experience with that package, here are some excellent online resources for building your R skills.
Who should register?
If you want to learn how to apply structural equation models to binary and ordinal data and have a solid background in structural equation modeling, then this course is for you.
If you want to learn how to apply structural equation models to binary and ordinal data and have a solid background in structural equation modeling, then this course is for you.
Seminar outline
The proposed schedule follows an organized sequence: 1) Foundational components, 2) Structural components, 3) Measurement components, and 4) Advanced issues and applications.
Day 1: Foundational components
-
- Overview of structural equation modeling
- Introduction to R and Mplus syntax
- Logistic and probit regression models
- Implementation in R and Mplus
Day 2: Structural components
-
- Cumulative logit and probit regression models
- Implementation in R and Mplus
- Path models with binary and ordinal mediators and outcomes
- Model specification, estimation, evaluation, interpretation
- Implementation in R and Mplus
Day 3: Measurement components
-
- Confirmatory factor analysis with binary and ordinal indicators
- Model specification, estimation, evaluation, interpretation
- Implementation in R and Mplus
- Structural equation models with binary and ordinal indicators
- Model specification, estimation, evaluation, interpretation
- Implementation in R and Mplus
Day 4: Advanced issues and applications
-
- Multiple-group confirmatory factor analysis with binary and ordinal indicators
- Measurement invariance testing
- Missing data handling with binary or ordinal variables
- Review of count regression models (time permitting)
- Count regression models in Mplus
The proposed schedule follows an organized sequence: 1) Foundational components, 2) Structural components, 3) Measurement components, and 4) Advanced issues and applications.
Day 1: Foundational components
-
- Overview of structural equation modeling
- Introduction to R and Mplus syntax
- Logistic and probit regression models
- Implementation in R and Mplus
Day 2: Structural components
-
- Cumulative logit and probit regression models
- Implementation in R and Mplus
- Path models with binary and ordinal mediators and outcomes
- Model specification, estimation, evaluation, interpretation
- Implementation in R and Mplus
- Cumulative logit and probit regression models
Day 3: Measurement components
-
- Confirmatory factor analysis with binary and ordinal indicators
- Model specification, estimation, evaluation, interpretation
- Implementation in R and Mplus
- Structural equation models with binary and ordinal indicators
- Model specification, estimation, evaluation, interpretation
- Implementation in R and Mplus
- Confirmatory factor analysis with binary and ordinal indicators
Day 4: Advanced issues and applications
-
- Multiple-group confirmatory factor analysis with binary and ordinal indicators
- Measurement invariance testing
- Missing data handling with binary or ordinal variables
- Review of count regression models (time permitting)
- Count regression models in Mplus
- Multiple-group confirmatory factor analysis with binary and ordinal indicators
Payment information
The fee of $995 USD includes all course materials.
PayPal and all major credit cards are accepted.
Our Tax ID number is 26-4576270.
The fee of $995 USD includes all course materials.
PayPal and all major credit cards are accepted.
Our Tax ID number is 26-4576270.