Applied Longitudinal Data Analysis

Instructor: Stavroula Chrysanthopoulou
Textbook: Fitzmaurice, G.M., Laird, N.M. and Ware, J.H. (2011). Applied Longitudinal Analysis (2nd Edition). Wiley Publishing. ISBN 978-0-470-38027-7.

Description: This course was designed for graduate and advanced undergraduate students who want to develop a practical hands-on toolkit for and/or understand the theoretical underpinnings of longitudinal data analysis and modeling. Additionally, it provided a foundation for statistical thinking in clinical and population health research involving longitudinal data. Topics ranged from exploratory analysis, study design considerations, covariance structures, and modeling approaches for longitudinal data, including marginal and mixed effects generalized linear models for both continuous and categorical outcomes. Extensive use of computer programming, particularly in R and STATA, was required to analyze longitudinal data from a range of medical and pharmaceutical applications, as well as public health and the social sciences.

By considering the time component, researchers can detect changes over time, assess the impact of covariates, and forecast future trends.

Assignments:

• Homework 1
• Homework 2
• Homework 3

 

Spring ‘22