Structural equation modeling using Stata

4 days 3–4 hours daily

This course introduces structural equation modeling and its implementation in Stata. Stata allows for fitting structural equation models in two ways—by using the command syntax or using the SEM Builder to draw path diagrams. Examples will demonstrate both approaches, starting with linear regression up to confirmatory factor analysis and growth curve modeling. Model identification and evaluation will also be extensively discussed. The course concludes with a brief introduction to multilevel models and generalized linear models within the SEM framework.

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Upcoming sessions

23–26 February 2027

11:00 a.m. to 2:30 p.m. CST (5:00 p.m. to 8:30 p.m. UTC)

Enrollment deadline: 19 February

Enroll via Instats

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Course leader

Meghan Cain

Assistant Director, Educational Services

Meghan Cain is the Assistant Director of Educational Services at StataCorp LLC. 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 oversees training courses, webinars, and videos, and develops and presents many of them herself. She also reviews Stata Press books and provides statistical expertise for marketing content.

Prerequisite

A general familiarity with Stata and a graduate-level course in regression analysis or comparable experience.

Course topics

Overview of linear structural equation modeling

Model description
Process of fitting and evaluating structural equation models
Description of path diagrams

Stata’s tools for SEM

Fitting models with the sem command
Fitting models with the SEM Builder by drawing path diagrams
Using the ssd commands to work with summary statistics

Details on specific types of structural equation models

Models with observed variables

Linear regression
Path analysis
Mediation analysis

Models with latent and observed variables

Confirmatory factor analysis
Full structural equation models
Latent growth curves

Models with multiple groups

Testing and interpreting linear SEM results

Standardized results
Direct, indirect, and total effects
Goodness-of-fit statistics
Modification indices
Model comparison

Overview of generalized structural equation modeling and the gsem command

Fitting multilevel models
Fitting models with binary, ordered, count, and categorical outcomes

Report results from a structural equation modeling analysis

Future sessions

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