Latent Class Analysis and Regression for Mental Health Research
- East Baltimore
- Summer Inst. term
- Mental Health
- 2 credits
- Academic Year:
- 2017 - 2018
- Tue 06/06/2017 - Wed 06/07/2017
- Class Times:
- Tu W, 8:30am - 5:00pm
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:
- Identify appropriate applications of latent class analysis
- Describe the latent class analysis model, including each parameter and its interpretation
- Fit latent class analytic models using MPLUS
- 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.