Latent Profile Analysis

Quantitative Methods Workshop Series

This is a 2-day online course that takes place on May 15, & 16 (Monday & Tuesday, 10:00 am - 4:30 pm).

Latent profile analysis (LPA) reflects a series of statistical models that can be used to investigate the presence and nature of unobserved heterogeneous, qualitatively distinct subgroups. LPA is nested within the broader family of structural equation models (referred to as mixture models) and is increasingly being used in numerous areas of research. This course will introduce LPA, focusing on applications in the social, educational, health, and management sciences. This course will provide participants with the theoretical and conceptual background and applied analytical skills needed to specify an appropriate analytical model, interpret the results, and thoroughly address research questions using LPA that involve predictors and outcomes of membership in the estimated subgroups. This course offers lectures that feature worked examples, numerous hands-on activities and practice sessions, as well as ample opportunities to discuss participants’ own LPA-based research ideas.

This course will use the R and Mplus software packages and will supply participants with the syntax and knowledge to thoroughly conduct advanced LPA-based research into a wide range of empirical domains. (for those individuals who do not have an Mplus license, the free demo version is available at http://statmodel.com/demo.shtml and will be sufficient for any Mplus-based activities completed.)

Beyond p-values: Modern Statistical Thinking in Psychology

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Introduction to Bayesian Modeling

Introduction to Python for Data Analysis

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Latent Profile Analysis

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Latent Profile Analysis

More events from Quantitative Methods Workshop Series

Follow organizers to get events picked for you

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