140.655.01 ANALYSIS OF LONGITUDINAL DATA

Explores statistical models for drawing scientific inferences from longitudinal data. Topics include longitudinal study design; exploring longitudinal data; linear and generalized linear regression models for correlated data, including marginal, random effects, and transition models; and handling missing data. Intended for doctoral students in quantitative sciences.

Upon successfully completing this course, students will be able to: 1) prepare graphical or tabular displays of longitudinal data that effectively communicate the patterns of scientific interest; 2) implement and interpret a general linear model to make scientific inferences about the relationship between response and explanatory variables while accounting for the correlation among repeated responses for an individual; 3) implement and interpret marginal, random effects, or transitional generalized linear models to make scientific inferences when the repeated observations are binary, counts, or non-Gaussian continuous observations; 4) implement analysis of longitudinal data within SAS or STATA.