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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 3-Day Remote Seminar Taught by Kevin Grimm, 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. 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).

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.