140.655.01 ANALYSIS OF LONGITUDINAL DATA
- Elizabeth Colantuoni
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.
- Monday 10:30 - 11:50
- Wednesday 10:30 - 11:50
- Monday 9:00 - 10:20
- Wednesday 9:00 - 10:20
140.621-624, former 140.601-604, or 140.651-654