Bethany Bray, PhD
Associate Director for Scientific Outreach, CDIS
Associate Professor, Department of Medicine
Friday, July 17, 2020
9:00am-12:00pm, 1:30pm-4:00pm
Workshop via Zoom
Please register in advance for this event:
https://uic.zoom.us/meeting/register/tJIpfuqqpzojE9VI8lvSQmh0l690tSEgSJvy
Workshop objective: The goal of this one-day workshop is to help participants gain the theoretical background and applied skills to be able to address interesting research questions using latent class analysis. By the end of the workshop, participants will have learned how to fit a preliminary latent class model to data. Participants will become familiar with introductory latent class 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 Sciences.
General description: Workshop time will be spent in lecture, software demonstrations, computer exercises, and discussion. At the workshop, participants will be provided with files containing all lecture notes, select computer exercises and output, and suggested reading lists for future reference. The software demonstrated in this workshop will be SAS and/or Mplus.
Prerequisites: 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 or Mplus and logistic regression is helpful, but not a prerequisite.
Computer requirements: Participants are encouraged to join the virtual workshop from a laptop or desktop computer so that they can conduct the computer exercises and analyze their own data. To conduct analyses at the workshop, SAS V9 or Mplus Version 8 must be installed on the computer prior to the workshop. Simulated data sets will be made available to participants for use during and after the workshop.
Topics to be covered: Introduction to latent class analysis (LCA) and the LCA model; model interpretation, model selection, and model identification; multiple-groups LCA and measurement invariance across groups; LCA with covariates; LCA with distal outcomes
In addition to the above topics, there will be open discussion times and question/answer periods.
1Collins, L. M., & Lanza, S. T. (2010). Latent class and latent transition analysis: With applications in the social, behavioral, and health sciences. New York: Wiley.