Introduction to Latent Class and Latent Transition Analysis

June 6th & 7th

103 SWKT


Bethany C. Bray, Ph.D.

Bethany C. Bray, PhD is a Research Associate in The Methodology Center at Penn State. She received a Masters in Applied Statistics in 2006 and a PhD in Human Development and Family Studies in 2007 from Penn State. Dr. Bray’s research focuses on the development and application of advanced latent class modeling techniques to questions about the development of alcohol and other substance use, with a special emphasis on its relation to the development of comorbid risk behaviors like gambling and risky sexual behavior. Her dissertation work, focusing on the application of latent class modeling techniques in gambling research, received the Outstanding Dissertation Award from the National Council on Problem Gambling. Dr. Bray’s research has been funded through NIH and the Alcohol Beverage Medical Research Foundation (ABMRF), and has been published in a variety of methodological and substantive journals. Dr. Bray has taught graduate-level courses on research methods, psychometrics, and categorical data analysis, as well as hands-on workshops on latent class/transition analysis and programming in SAS and R. She has extensive experience presenting technical material to applied scientists. For more information, visit her website at


The goal of this two-day workshop is to help you gain the theoretical background and applied skills to be able to address interesting research questions using latent class and latent transition analysis. By the end of the workshop, participants will have fit preliminary latent class and latent transition models to data provided by the presenter. Participants will become familiar with all of the latent class analysis concepts, and many of the latent transition analysis concepts, covered in the recent book co-authored by Drs. Linda Collins and Stephanie Lanza and published by Wiley, Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences1.

Workshop time will be spent in lecture, software demonstrations, computer exercises, and discussion. At the workshop, participants will be provided with a hard copy of all lecture notes, select computer exercises and output, and suggested reading lists for future reference. The software used in this course is PROC LCA and PROC LTA, a downloadable add-on procedure for SAS to conduct latent class and latent transition analysis that is developed at the Penn State Methodology Center.


  • ​Introdu​ction​ to latent class analysis (LCA) and the LCA model​​​
  • Model interpretation, model selection, model identification
  • Multiple-groups LCA
  • Measurement invariance across groups​
  • Review of logistic regression​
  • LCA with covariates
  • LCA with distal outcomes
  • Introduction to latent transition analysis (LTA) and the LTA model
  • Measurement invariance across time
  • Multiple-groups LTA
  • LTA with covariates


The prerequisite for this workshop is graduate-level statistics training for the behavioral or health sciences up through linear regression (usually two semesters of course work). Basic familiarity with SAS and logistic regression is helpful, but not a prerequisite. The software used in this course, the newly released versions of PROC LCA and PROC LTA, is available on the lab computers.

There is no fee for the workshop, but registration online is required Any questions or requests for further information can be directed to Chongming Yang at the College's Research Support Center. (801) 422-5694.​​​​​