330.666.11 LONGITUDINAL ANALYSIS WITH LATENT VARIABLES

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.

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