Categorical Structural Equation Modeling

A 3-Day Remote Seminar Taught by
Kevin Grimm, Ph.D.

Read reviews from other seminars taught by Kevin Grimm

To see a sample of the course materials, click here.

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. That’s 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 May 6, we are offering this seminar as a 3-day synchronous*, remote workshop for the first time. Each day will consist of a 4-hour live lecture held via the free video-conferencing software Zoom. You are encouraged to join the lecture live, but will have the opportunity to view the recorded session later in the day if you are unable to attend at the scheduled time.

Each lecture session will conclude with a hands-on exercise reviewing the content covered, to be completed on your own. An additional lab session will be held Thursday and Friday afternoons, where you can review the exercise results with the instructor and ask any questions.

*We understand that scheduling is difficult during this unpredictable time. If you prefer, you may take all or part of the course asynchronously. The video recordings will be made available within 24 hours of each session and will be accessible for two weeks after the seminar, meaning that you will get all of the class content and discussions even if you cannot participate synchronously.


The following statistical models will be discussed:

  • logistic and probit regression and path models
  • cumulative logit and probit regression and path models
  • confirmatory factor models for binary and ordinal indicators (e.g., 2-parameter logistic model, graded response model)
  • multiple group confirmatory factor models for binary and ordinal indicators
  • latent growth models for binary and ordinal outcomes
  • survival analysis models.


This remote seminar is held via Zoom, a free video conferencing application. Instructions for joining a session via Zoom are available here. Before the seminar begins, you will receive an email with the meeting code and password you must use to join.

This seminar will use R and Mplus for the empirical examples and exercises. To participate in the hands-on exercises, you should have a computer with either Mplus or R installed.  If you are an R user, you should also install RStudio, a freely available interface for R, and the lavaan package for SEM. 

If you’d like to use R for this course but don’t yet have much experience with that package, here are some excellent on-line 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. Familiarity with either R or Mplus is strongly advised.


Day 1: Structural Equation Modeling with Binary Outcomes

  • Introduction to structural equation modeling
  • Review of logistic and probit regression in R
  • Introduction to Mplus and lavaan notation
  • Logistic and probit regression in Mplus and lavaan
  • Maximum likelihood estimation and weighted least squares estimation
  • Path models with binary mediators and outcomes
  • Confirmatory factor models with binary indicators
  • Model fit for maximum likelihood and weighted least squares estimators

Day 2: Structural Equation Models for Ordinal Outcomes

  • Cumulative logit and probit regression models in R
  • Cumulative logit and probit regression models in Mplus and lavaan
  • Confirmatory factor models with ordinal indicators
  • Latent variable path models with binary and ordinal indicators
  • Multiple group factor analysis with binary and ordinal indicators
  • Missing data handling with maximum likelihood and weighted least squares estimators

Day 3: Longitudinal Structural Equation Models for Binary and Ordinal Outcomes; Count Outcomes

  • Latent growth models with binary and ordinal outcomes
  • Survival analysis
  • Review of count regression models in R
  • Count regression models in Mplus
  • Zero-inflated count regression models in Mplus


“The course is beyond helpful. Professor Grimm obviously has a deep understanding of the material, and he is very effective at answering participant questions. The help and resources he provides defintely go beyond what I expected. I would recommend this course.”
  Alex Marbut, University of Alabama

“Kevin Grimm is an excellent instructor with many great relatable examples and funny stories. The methods were easy to follow and intuitive, and syntax was clear. Matches the high quality offered by other Statistical Horizons courses.”
  Andy Kin On Wong, University of Toronto / University Health Network

“Dr. Grimm was a wonderful, helpful, and articulate instructor who clearly knows the subject so well and is eager to help others also understand this broad statistical approach. He starts with the basics and quickly works his way up to more advanced topics – making the course suitable to a broad audience. I would highly recommend this class.”
  Linzy Bohn, University of Alberta

“The course was fantastic. Kevin Grimm is a fabulous instructor – great pace, plenty of examples are provided, and the slides are clear and easy to follow. I would highly recommend the course to colleagues. The materials provided for exercises and practice are plenty and instructions are very clear.”
  Grettel Castro, Florida International University

“Dr. Grimm is an outstanding instructor. The examples were useful and he is able to answer questions expertly.”
  Brent Small, University of South Florida

“Grimm covers a considerable number of complex topics in a very efficient way. Clearly he has been teaching this material for a long time.”
  Anibal Perez-Linan, University of Notre Dame