Graduate Course Directory and Schedules

This course is designed for students who have taken the basic applied statistical courses and wish to learn the more advanced statistical methods for longitudinal data. Longitudinal data consist of measurements of response variables at two or more points in time for many individuals. This course covers the statistical properties of longitudinal data and special challenges due to the repeated measurements on each individual, exploratory methods and statistical models for longitudinal data as well as some exposure to estimation methods and statistical properties of coefficient estimates. For statistical methods, the course will briefly mention the traditional repeated measure analysis of variance (ANOVA) approach for continuous data, and focus more on mixed effects model approach and estimation based on generalized estimating equation. Real life examples will be used to explain the concept and application of these models by using continuous, binary and count data. Homework assignments and final class project play a central role to understand and appropriately apply the methods covered in the course.

Prerequisites:

• BSTA 511/611: Estimation and Hypothesis Testing for Applied Biostatistics
• BSTA 512/612: Linear Models
• BSTA 513/613: Categorical Data Analysis