Free Introduction to Structural Equation Modeling

Replay Access: 1 year
Original Livestream: May 10-12, 2023
Instructors: Dan Bauer & Patrick Curran

Free Tuition

We have long been committed to providing broad access to high-quality training opportunities for students in the social, behavioral and health sciences. We are thus very excited to offer a repeat of our *completely free* three-day workshop, Introduction to Structural Equation Modeling, focused on the application and interpretation of statistical models that are designed for the analysis of multivariate data with latent variables. Although the traditional multiple regression model is a powerful analytical tool within the social sciences, this is also highly restrictive in a variety of ways. Not only are all variables assumed to have no measurement error, but it is also limited to a single dependent variable with unidirectional effects. The structural equation model (SEM) generalizes the linear regression model to include multiple dependent variables, reciprocal effects, indirect effects, and the estimation and removal of measurement error through the inclusion of latent variables. The SEM is a general framework that allows for the empirical testing of research hypotheses in ways not otherwise possible. In this workshop we provide a introduction to SEM that includes path analysis, confirmatory factor analysis, and structural equation models with latent variable and which focuses on both establishing a conceptual understanding of the model and how it is applied in practice.

Instructors

Daniel J. Bauer, Ph.D.

Dan Bauer is a Professor and the Director of the L.L. Thurstone Psychometric Laboratory in the Department of Psychology and Neuroscience at the University of North Carolina. He teaches primarily graduate-level courses in statistical methods, for which he has won multiple teaching awards. Read More

Patrick J. Curran, Ph.D.

Patrick Curran is a Professor in the L.L. Thurstone Psychometric Laboratory in the Department of Psychology and Neuroscience at the University of North Carolina at Chapel Hill. He is dedicated to teaching and disseminating advanced quantitative methods and has won multiple awards for teaching excellence. Read More

Workshop Details

Syllabus

Chapter 1. Introduction, Background, & Multiple Regression
1.1 Introduction
1.2 A Brief Introduction to Matrix Algebra
1.3 Linear Regression as a Structural Equation Model
1.4 Limitations of the Multiple Regression Model

Chapter 2. Path Analysis: Introduction
2.1 The Path Analysis Model
2.2 Model Identification
2.3 Model Estimation

Chapter 3. Path Analysis: Advanced Topics
3.1 Assessing Model Fit
3.2 Model Comparisons
3.3 Model Respecification and Modification Indices
3.4 Testing Direct and Indirect Effects
3.5 Assumptions (Self-Study)

Chapter 4. Confirmatory Factor Analysis
4.1 Confirmatory Factor Analysis
4.2 Issues and Extensions (Self-Study)

Chapter 5. Structural Equation Models with Latent Variables
5.1 Introduction to Structural Equation Models
5.2 Fitting and Evaluating Structural Equation Models
5.3 Additional Considerations: Estimation with Non-normal Distributions, Computing Power, and Equivalent Models (Self-Study)

Who Should Attend and Software Considerations

This workshop is broadly targeted towards research applications in behavioral, health, educational and psychological sciences, although the methods apply to many other disciplines as well. We recommend that participants have a working knowledge of the general regression model. Those who need a refresher may wish to check out episodes on our linear regression playlist on YouTube.

Software demonstrations are provided in R, Mplus, and Stata. Note that R can be downloaded for free. While it is helpful to have some familiarity with one of these software programs, this is not necessary. The lectures which constitute the majority of the workshop are software-independent

The Goals of the Workshop

Our motivating goal is to provide an intense yet enjoyable instructional experience. We strive to strike an equal balance between core concepts of the underlying statistical model along with the practical application and interpretation of structural equation models fitted to real empirical data. Our workshop is designed to provide participants with the materials and instruction needed to both develop a real understanding of structural equation models and to be able to thoughtfully apply a variety these models to their own data.

What is Provided

Availability of Recordings

Sample Content

Reviews

In an effort to continually improve our instruction we obtain student evaluations with each course offering. Here is a sample of reviews from our prior offering of this workshop:

Dan and Patrick do an awesome job at breaking down complex material and provide great applicable examples that really help with understanding and clarifying the concepts. The notes and materials provided are excellent and very detailed!

The workshop had a relaxed environment with plenty of banter. It was easy to follow the step-by-step workshop. As a result, I was able to learn a lot in a short amount of time.

Clear examples, software demonstrations/code, nice pacing (I appreciated the background information!). I was also extremely impressed by how responsive Dan/Patrick/Ethan were to participant questions!

Using real data to show examples and providing notes detailed for actually conducting the analyses later. The balance of what the theory is with the practical application is what my previous stats training often lacked (too little application).

The key strength was the clarity of communication and the balance between technicalities and intuition. Dr. Curran & Dr. Bauer did not shy away from technical aspects of the content but also communicated about them as intuitively as possible.

Dr. Curran and Dr. Bauer's style of lecture made complex statistical concepts straightforward and non-intimating, the lecture notes were very clear and the ability to ask questions via chat during lecture was amazing.

I have a much better understanding of what data modeling is. Before the workshop, I knew how to do SEM and even wrote a paper currently under review using SEM, but I didn't really understand what I was doing, why I was doing it, how it was being done

High quality materials and explanations. Very engaging to listen to.

The instructors were incredible. The way they taught complex concepts made things that were difficult for me to grasp previously magically fall into place. Concepts were clear and analogies were entertaining and on point!

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Free Introduction to Structural Equation Modeling

Instructors

Daniel J. Bauer, Ph.D.

Patrick J. Curran, Ph.D.

Workshop Details

Reviews

Quick Navigation

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