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Department: Mental Health
Term: Summer Inst. term
Credits: 3 credits
Contact: Shaunna Clark
Academic Year: 2012 - 2013
Course Instructor:
  • Shaunna Clark

Acquaints students with the use of latent variables in longitudinal data analysis as it is conceptualized in the Mplus framework. Focuses on modeling opportunities for observed categorical (binary and ordinal) and count variables with both continuous and categorical latent variables. Using standard linear regression models as a point of departure, covers binary and ordinal logistic regression; latent growth curve models with binary and ordinal outcome variables; Poisson regression; Poisson and zero-inflated Poisson (ZIP) latent growth curve models; discrete- and continuous-time survival analysis; and latent transition analysis. Students study examples drawn from available public date sets.

Learning Objective(s):

Upon successfully completing this course, students will be able to: to be added at a later date

Methods of Assessment: Based on active participation and written lab reports.
Location: East Baltimore
Class Times:
  • Mon 06/11/2012 - Wed 06/13/2012
  • Monday 9:00 - 5:00
  • Tuesday 9:00 - 5:00
  • Wednesday 9:00 - 5:00
Enrollment Minimum: 6
Instructor Consent: No consent required

330.657 and 140.658 (2 terms) or equivalent

Auditors Allowed: Yes, with instructor consent
Grading Restriction: Letter Grade or Pass/Fail
Frequency Schedule: