Latent Class Analysis - Online Course

This seminar is part of the Measurement and Psychometrics Certification, a series of 4 expert-led courses designed to provide advanced training and build specialized skills in measurement science. Contact us to learn how to complete your certification and access special pricing.

Latent Class Analysis (LCA) provides empirical researchers in the social, behavioral, and health sciences with a critical lens through which to inspect their data. This method has the ability to uncover hidden structures and patterns related to complex phenomena. For example, LCA enables social scientists to discover subgroups within a population that share similar patterns of behaviors or attitudes. Researchers can also gain a more nuanced understanding of human behavior by using LCA to characterize patterns of intersecting behaviors that confer a high risk of adverse outcomes.

LCA can be viewed as a special kind of structural equation modeling in which the latent variables are categorical rather than continuous. This seminar will give you the theoretical background and applied skills to address interesting research questions using LCA. Topics include model identification, model selection, model interpretation, multiple-groups LCA, measurement invariance across groups, LCA with covariates and outcomes, and latent profile analysis (LPA). The format will combine lectures, software demonstrations, computer exercises, and discussion. There will be opportunities to discuss how LCA can be applied in your own research.

Using LCA to gain new insight into how different components interact and influence outcomes, researchers can gain a more comprehensive understanding of phenomena under investigation. Applying this technique to empirical data can inform theory, contribute to evidence-based decision-making, and guide development of interventions tailored to specific subgroups within a population. Ultimately, LCA empowers empirical researchers in the social, behavioral, and health sciences to extract new insights from their data and contribute innovative findings that advance science.

Starting October 29, this seminar will be presented as a 3-day synchronous, livestream workshop via Zoom. Each day will feature two lecture sessions with hands-on exercises, separated by a 1-hour break. Live attendance is recommended for the best experience. If you can’t join in real time, recordings will be available within 24 hours and accessible for four weeks after the seminar.

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

ECTS Equivalent Points: 1