Structural Equation Modeling with Categorical Data – July 2026

Event Phone: 1-610-715-0115

Details Price Qty
Regular Admissionshow details + $995.00 USD  ea 

Upcoming Dates

  • 07
    Jul
    Structural Equation Modeling with Categorical Data
    10:30 AM
    -
    3:00 PM
Cancellation Policy: If you cancel your registration two weeks or more before the course is scheduled to begin, you are entitled to receive your choice of either a credit for a future seminar (which can be applied toward any of our courses) or a refund of the registration fee (minus a processing fee of $50). 
In the unlikely event that Statistical Horizons LLC must cancel a seminar, we will do our best to inform you as soon as possible of the cancellation. You would then have the option of receiving a full refund of the seminar fee or a credit towards another seminar. In no event shall Statistical Horizons LLC be liable for any incidental or consequential damages that you may incur because of the cancellation.
A 4-Day Livestream Seminar Taught by Sonja Winter, Ph.D.

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).

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.

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