Analysis of Longitudinal Data
June 19-23, 2017
8:30 a.m. - 12:00 p.m.
Course Number: 140.608.11
Covers 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. Enrollment limited; students are required to bring a laptop to class, with Stata 11 or 12 installed. Contact Ayesha Khan (email@example.com) to find out how to get STATA through the Stata GRADPLAN.
Student Evaluation: Student evaluation based on analysis of a longitudinal data set, presentation of the results, and a written scientific report of the analysis methods and results
Learning Objectives: Upon successfully completing this course, students will be able to:
- Prepare graphical or tabular displays of longitudinal data that effectively communicate the patterns of scientific interest
- Use 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
- Use marginal, random effects, or transitional generalized linear models to make scientific inferences when the repeated observations are binary, counts, or non-Gaussian continuous observations
- Use SAS or STATA to conduct the appropriate longitudinal data analyses.
Prerequisites: Intermediate level biostatistics and epidemiology
Grading Options: Letter Grade or Pass/Fail
Course Materials: Provided in class
Recommended Textbook: Multilevel and Longitudinal Modeling Using Stata, Third Edition, Sophia Rabe-Hesketh and Anders Skrondal