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Longitudinal Data Analysis Using Structural Equation Modeling - Online Course

A 4-Week On Demand Seminar Taught by

Paul Allison
Course Dates:

Monday, January 23 —
Monday, February 20, 2023

Schedule:

Each Monday you will receive an email with instructions for the following week.

All course materials are available 24 hours a day. Materials will be accessible for an additional 2 weeks after the official close on February 20.

Watch Sample Video

For the past seven years, Dr. Paul Allison has been teaching his acclaimed seminar on Longitudinal Data Analysis Using Structural Equation Modeling to audiences around the world. This seminar develops a methodology that integrates two widely used approaches to the analysis of longitudinal data: cross-lagged panel analysis and fixed effects analysis. In this more comprehensive framework, you can test causal hypotheses in a way that both controls for unmeasured confounders while also allowing for reverse causation. In addition, the SEM methodology lets you relax many of the restrictive assumptions of more traditional methods.

The course takes place in a series of four weekly installments of videos, quizzes, readings, and assignments, and requires about 6-8 hours/week. You can participate at your own convenience; there are no set times when you are required to be online. The course can be accessed with any recent web browser on almost any platform, including iPhone, iPad, and Android devices. It consists of 11 modules:

    1. Introduction
    2. Cross-Lagged Panel Models
    3. Goodness of Fit and Equality Constraints
    4. Fixed Effects with SEM
    5. Fixed Effects with Time-Invariant Predictors
    6. Combining Fixed Effects with Cross-Lagged Models
    7. One-Sided Estimation
    8. Hip Data Example
    9. Getting the Lags Right
    10. Models for Binary Outcomes
    11. Models for Count Data

The modules contain videos of the live, 2-day version of the course in its entirety. Each module is followed by a short multiple-choice quiz to test your knowledge. There are also weekly exercises that ask you to apply what you’ve learned to a real data set.

Each week, there are two assigned articles to read. There is also an online discussion forum where you can post questions or comments about any aspect of the course. All questions will be promptly answered by Dr. Allison.

Downloadable course materials include the following PDF files:

    • All slides displayed in the videos.
    • Exercises for each week.
    • Readings for each week.
    • Computer code for all exercises (in SAS, Stata, Mplus and R formats).
    • A certificate of completion.

More details about the course content

Computing

Who should register?

Registration instructions

"Numerous exercises support an understanding of the content..."

“The course opens an excellent introduction to longitudinal data analysis. Personally, what I like most is that frequently occurring problems, such as getting the lags right, are specifically addressed, discussed clearly, and also solved in a comprehensible manner. Numerous exercises support an understanding of the content and enable the participants to apply what they have learned in practice – including their own research. Moreover, there is a lively discussion about the topic. Questions of the participants are answered promptly and to their satisfaction.” 

Thomas Zimmermann

Goethe University Frankfurt 

"The assignments were very helpful to apply what we learned.” 

“The length of the videos was very manageable. The assignments were very helpful to apply what we learned.” 

Lieke ten Brummelhuis

Simon Fraser University 

"This seminar was very informative as I have been needing help with my research on longitudinal data."

“This seminar was very informative as I have been needing help with my research on longitudinal data. I really appreciate Dr. Allison’s patience in explaining concepts for me, even basic questions about the concepts and software. I really appreciated this as this analysis method didn’t seem as daunting an undertaking as I had anticipated given the great explanations during the class.”

Emma Lu

“The structure of the course content, the video lectures, the readings, and the homework exercises were all excellent.”

“The structure of the course content, the video lectures, the readings, and the homework exercises were all excellent.”

Yang Yang

Rowan University

“I would recommend anyone interested in SEM take this course."

“I would recommend anyone interested in SEM take this course. It is very pedagogical and the pace is neither too fast nor too slow. You will learn a lot, and you will get both a basic and more advanced understanding of SEM.”

Dennis Andersson

University of Gothenburg

"The online format offers a lot of advantages to participants..."

“This was an excellent course covering an important analytical approach to longitudinal data analysis. Dr. Allison is both a pioneer in this method and an excellent teacher. The online format offers a lot of advantages to participants who wish to revisit materials and ask Dr. Allison carefully considered questions. I highly recommend this course.”

Xiaoquan Zhao

George Mason University

"I feel this course really opened another window for me..."

“I studied this course after taking an econometric class. I feel this course really opened another window for me to think about similar things in a different way, which is quite enlightening.”

Ying Liang

Wuhan University