Latent Class Analysis is a method for finding and measuring unobserved latent subgroups in a population based on responses to a set of observed categorical variables.
This webinar will present an overview and an example of how latent class analysis works to find subgroups, how to interpret the output, the steps involved in running it. We will discuss extensions and uses of the latent classes in other analyses and similarities and differences with related techniques.
Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and part of the Stat’s Amore Trainings Series. Each Stat’s Amore Training is approximately 90 minutes long.
About the Instructor
Karen Grace-Martin helps statistics practitioners gain an intuitive understanding of how statistics is applied to real data in research studies.
She has guided and trained researchers through their statistical analysis for over 15 years as a statistical consultant at Cornell University and through The Analysis Factor. She has master’s degrees in both applied statistics and social psychology and is an expert in SPSS and SAS.
Just head over and sign up for Statistically Speaking. You'll get access to this training webinar, 130+ other stats trainings, a pathway to work through the trainings that you need — plus the expert guidance you need to build statistical skill with live Q&A sessions and an ask-a-mentor forum.
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