Introduction to Structural Equation Modeling

Structural equation modeling (SEM) offers tremendous modeling flexibility that simpler instantiations of the general linear model (e.g., multiple regression, ANOVA, factor analysis) just can't handle. This workshop will teach you to elevate your modeling by teaching you the fundamentals of SEM.

Instructor:
Aidan Wright, PhD (University of Michigan)

Workshop Dates and Times:
Monday, May 13th, 10:00am – 3:30pm ET
Tuesday, May 14th, 10:00am – 3:30pm ET
Wednesday, May 15th, 10:00am – 3:30pm ET

Workshop Format:
Three-Day Synchronous Online Workshop

This 3-day workshop will offer a basic introduction to the principles of modern structural equation modeling (SEM), with an emphasis on the applied use of these techniques. The goal is to provide attendees with a strong set of fundamentals that will allow them to flexibly apply SEM to answer diverse questions in a wide variety of data. Core topics covered will include conceptual introduction to latent variable models, fundamentals of covariance structure models (e.g., data requirements, identification, etc.), measurement models and confirmatory factor analysis, path analysis, and full SEM. Advanced topics, including multiple group analysis, measurement invariance, and SEM with categorical data will be covered based on time availability.

What you’ll learn

  • Fundamentals - Understand the fundamental issues associated with latent variables, path analysis, and related issues.

  • Design – Learn how to design and estimate SEMs in the popular statistical software platforms Mplus and the lavaan package in R.

  • Interpretation – Develop the interpretive skills to extract valuable insights from SEMs.

  • Unlock new insights – Learn how SEM software can be used to do more powerful and confirmatory analyses for even very simple models (e.g., standard regression).

Syllabus

Day 1:

  1. Overview of SEM

  2. Foundations of Path Analysis

  3. Path Analysis Estimation

  4. Overview of Model Fit

Day 2:

  1. Foundations confirmatory factor analysis (CFA)

  2. CFA Estimation

  3. Integration of path analysis and CFA in full SEMs

Day 3:

  1. Introducing mean vectors

  2. Multiple Group Analysis

  3. Non-Normal and categorical data analysis

  4. Use of full information maximum likelihood for missing data

Registration Options

Introduction to Structural Equation Modeling

  • Professional
  • $449
  • Baseline Price for Faculty,
    Staff, and Other Professionals
  • Click Register Below
  • Trainee
  • $449 $299
  • 33% Discount for
    Students and Postdocs
  • Use code "TRAINEE" at Checkout

Combo 1: Introduction to Structural Equation Modeling + Longitudinal Structural Equation Modeling

  • Professional
  • $1273 $1019
  • Baseline Price for Faculty,
    Staff, and Other Professionals
  • 20% Combination Discount
  • Click Register Below
  • Trainee
  • $1019 $679
  • 33% Discount for
    Students and Postdocs
  • 20% Combination Discount
  • Use code "TRAINEE" at Checkout

 FAQs

  • This workshop is specially designed for researchers in the behavioral and health science who want to elevate their modeling with path analyses and latent variable modeling.

  • Intermediate

  • Basic graduate statistical training, including master of multiple regression is expected. No prior knowledge of or experience with structural equation models is necessary.

  • Mplus, Lavaan Package in R

  • Participants will be provided with annotated example code, practice data, and example write-up.