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Latent Class Analysis and Regression for Mental Health Research

East Baltimore
Summer Inst. term
Mental Health
2 credits
Academic Year:
2016 - 2017
Tue 06/07/2016 - Wed 06/08/2016
Class Times:
  • Tu W,  8:30am - 5:00pm
Auditors Allowed:
Yes, with instructor consent
Grading Restriction:
Letter Grade or Pass/Fail
Course Instructor :
Jeannie-Marie Sheppard
Frequency Schedule:
One Year Only

140.621-624 or equivalent.


Addresses latent class analysis, a latent variable method often used in Mental Health research to identify latent groups of individuals based on patterns of categorical observed variables. Use of additional variables to predict latent class membership will also be explored. Includes discussion of examples from the mental health literature as well as hands-on model-fitting using MPLUS. Latent class analysis is a method of modeling categorical latent variables, such as psychiatric diagnoses, as a function of a set of categorical observed variables.

Learning Objectives:

Upon successfully completing this course, students will be able to:

  1. Identify appropriate applications of latent class analysis
  2. Describe the latent class analysis model, including each parameter and its interpretation
  3. Fit latent class analytic models using MPLUS
  4. Assess concurrence with model assumptions and model fit
Methods of Assessment:

Independent data analysis project

Instructor Consent:

No consent required

Special Comments:

This will be classroom based. Students will be required to bring their own laptops. The MPLUS demo software is free.