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Latent Growth Curve Modeling - Online Course

A 3-Day Livestream Seminar Taught by

Dan McNeish
Course Dates:

Wednesday, December 10 –
Friday, December 12, 2025

Schedule: All sessions are held live via Zoom. All times are ET (New York time).

10:00am-12:30pm (convert to your local time)
1:30pm-3:30pm

Watch Sample Video

This course provides an introduction to latent growth curve modeling, a class of models within the structural equation modeling framework that can be used to model change or growth in longitudinal data.

The course is intended for those who are looking to familiarize themselves with growth modeling. No previous experience with longitudinal data is assumed. The emphasis of the course is to build a solid foundation for (1) why longitudinal data require specialized methods, (2) the opportunities and unique research questions that can be asked and answered with longitudinal data, (3) the conceptual underpinning of latent growth curve models and how they accommodate features of longitudinal data, and (4) when latent growth curve models may or may not be ideally suited to help researchers model their longitudinal data.

As a rudimentary outline for the course, we will begin with an overview of longitudinal data to contextualize how latent growth curve models fit into the broader landscape of longitudinal modeling and to identify the types of questions that latent growth models can help answer. Then, we will introduce the basic tenets of latent growth curve modeling. Lastly, we will cover some more advanced topics that routinely arise in empirical analyses.

Starting December 10, we are offering this seminar as a 3-day synchronous*, livestream workshop held via the free video-conferencing software Zoom. Each day will consist of two lecture sessions which include hands-on exercises, separated by a 1-hour break. You are encouraged to join the lecture live, but will have the opportunity to view the recorded session later in the day if you are unable to attend at the scheduled time.

*We understand that finding time to participate in livestream courses can be difficult. If you prefer, you may take all or part of the course asynchronously. The video recordings will be made available within 24 hours of each session and will be accessible for four weeks after the seminar, meaning that you will get all of the class content and discussions even if you cannot participate synchronously. 

Closed captioning is available for all live and recorded sessions. Live captions can be translated to a variety of languages including Spanish, Korean, and Italian. For more information, click here.

ECTS Equivalent Points: 1

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"It was an informative experience that will permanently shape how I analyze data for the rest of my career.”

“I’m an applied researcher, and Dr. McNeish does a great job of breaking down complicated concepts in a way that lets me not only understand how to use them, but also how to troubleshoot the errors I might encounter when fitting my data with growth trajectories. He provided example code for every type of model discussed in the statistical software I use. If someone had a tangential but relevant topic, he was also able to provide supplemental recommendations for analyses approaches in real time. His teaching is adaptive and practical. He’s amazing at answering questions. Although the course was taught through two provided example datasets, I was able to apply my own data during those portions of the lecture and have tailored questions answered immediately. It was an informative experience that will permanently shape how I analyze data for the rest of my career.”

Jynx Pigart

Arizona State University

"Dan was very good at explaining complex concepts in a simple way."

“I loved the in-depth explanation of the foundations of LGM. Dan was very good at explaining complex concepts in a simple way, and it was so helpful. I also loved the use of both path models, equations, and R code. So helpful!”

Amanda Cooper

University of Connecticut

"This was a well-structured and informative course."

“Dan was very clear in his explanations and combined with the detailed course resources, this was a well-structured and informative course. I would happily attend another of Dan’s courses, and I have recommended this course to my university.”

Jaana Haaja

Griffith University

"He was easy to follow, laid a solid foundation for the subject matter, and explained key concepts clearly."

“I enjoyed the instructor’s teaching style. He was easy to follow, laid a solid foundation for the subject matter, and explained key concepts clearly. He was also thorough when answering questions, which made the sessions engaging and informative. I also appreciated the ability to access class recordings, which made it possible to catch up on missed sessions.”

Tijesunimi Ojo

University of Edinburgh

"Anyone interested in longitudinal modeling should take this course.”

“Dan is a phenomenal teacher, and he makes everything clear. It was beyond helpful! Anyone interested in longitudinal modeling should take this course.”

Peter Bjorklund Jr.

University of California

“Dan was the best teacher I have ever had who taught a complex analytic method."

“Dan was the best teacher I have ever had who taught a complex analytic method. He repeated himself, went through the concepts slowly, stopped frequently for questions, and started at the very beginning. It was very effective. I loved the course and the teacher was excellent!”

Judy Harbertson

San Diego State University

"This is the best statistical course I have taken..."

“This is the best statistical course I have taken and I will recommend it to my team at my university. Although I could not join in the same time zone, I very much appreciated being able to watch the recordings, pause the videos, and add notes to the PDFs. It was an excellent course!”

Jennifer Wild

University of Oxford

"Overall, this course was excellent!”

“The instructor, Dan, did an outstanding job of laying a good foundation of concepts and then building on them at a pace that was easy to follow. The materials provided were well-organized, clear, and very easy to follow. I know I will be able to continue learning from the materials even after the class (a major plus). Dan did a great job addressing questions and seemed to be infinitely patient when we asked a lot of questions to clarify points. Overall, this course was excellent!”

Kelly Cara

Tufts University