Free Introduction to Structural Equation Modeling
May 11-13, 2022
Replay Access: 1 year from end of workshop
Instructors: Dan Bauer & Patrick Curran
Registration for this workshop is closed. Check out the Workshops page for asynchronous and upcoming livestream workshops.
Note: If you can't wait for the Livestream or it doesn't fit your schedule, consider registering for asynchronous access to the prior offering. You get all the same material at the same great price of free but can proceed at your own pace.
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.
Introduction to Structural Equation Modeling is a three-day workshop 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.
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. Patrick has dedicated much of his career to the teaching and dissemination of advanced quantitative methods and has won awards in recognition of teaching excellence. Read More
Hear the instructors talk about the class in this video interview conducted in 2021 (please note that the dates for this year differ).
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!