Mixture Modeling and Latent Class Analysis: A Short Course
January 3-5, 2024
10:00 am – 3:30 pm (Eastern US time)
Replay Access: 1 year from end of workshop
Instructor: Dan Bauer
Software Demonstrations: Pre-recorded in Mplus and R
Mixture Modeling and Latent Class Analysis is a three-day workshop focused on the application and interpretation of statistical techniques designed to identify subgroups within a heterogeneous population, including latent class analysis, latent profile analysis, and other finite mixture models. In practice, these methods are often implemented with the goal of identifying theoretically distinct subgroups (e.g., people with a liability for schizophrenia versus those without). Alternatively, they can be used as a data reduction device, to summarize prototypical patterns when working with complex multivariate data (e.g., market segmentation in consumer research). In recent years, an increasing focus has been on multivariate and longitudinal applications and identifying predictors or subgroup membership or distal outcomes. In this workshop we provide a comprehensive exploration of the foundations and uses of latent class/profile analysis and finite mixture models.
Note: This workshop is a shorter version of our 5-day Latent Class and Mixture Modeling workshop, which is currently available for self-paced access. The longer workshop includes two additional topics: (1) latent class moderation (in which latent class moderates the effect of one variable on another, such as the effect of treatment on an outcome varying by class); and (2) longitudinal mixture models, with a principal focus on growth mixture models. Those interested in these additional topics may prefer to enroll in the longer version of the class.
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
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 online offerings of Mixture Modeling and Latent Class Analysis:
Despite the common challenges of the online format, it was a very engaging course, easy to follow and very practice-oriented to provide the required skills to implement the analyses independently afterwards. I would highly recommend this course!
The lecture approach of presenting material followed by examples/demonstrations was helpful, as was having the live Q&A going simultaneously to allow for questions as the material was presented.
The topics are explained very thoroughly, with historical context, multiple examples, pros and cons of the approaches, and strategies to address potential problems
As a developmental psychologist, I appreciated all the examples presented in class.
I really enjoyed the pace of the course, the fact that we are able to re-watch the videos, and the demonstrations... I also appreciate the incredibly helpful details provided in the supporting materials.
I would highly recommend it! I really appreciated the balance between theory and application and that syntax files were provided so that we have them to build off of for our own analyses.
Good experience and very clear — very responsive to questions and mindful of a range of statistical expertise.
I love in person trainings, but travel can be hard, and expensive (especially as a grad student). The online format is so accessible, plus having access to recordings! And I really feel like y'all do an excellent job of making the sessions engaging.
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