Overview

Structural equation models (SEMs) can model a wide range of hypotheses. They can include latent constructs, such as depression, and their measurement models. Observed and latent variables can be modeled as both predictors and outcomes simultaneously, which is particularly useful for mediation analysis and longitudinal analysis.

Join Meghan Cain, Senior Statistician, for an introduction to SEM in Stata. In this webinar, you will learn about Stata's sem and gsem commands. You will see how they can be used to fit some common models, such as confirmatory factor models and regression models, and how they can fit models with both measurement and structural components. We will discuss SEM for continuous, categorical, ordinal, count, and other outcomes. We will work examples of multilevel and multigroup SEMs. You will also learn about tools for evaluating model fit.

How to join

The webinar is free, but you must register to attend. Registrations are limited so register soon.

We will send you an email prior to the start of the course with instructions on how to access the webinar.

Presenter: Meghan Cain

Meghan Cain is a Senior Statistician at StataCorp. She earned her PhD in quantitative psychology from the University of Notre Dame, where her research focused on structural equation modeling, multilevel modeling, and Bayesian statistics. At Stata, she develops and presents training on these and other topics. She also conducts webinars, works with developers to produce Stata documentation, and contributes to Stata blogs.