Module date/time: Monday, July 23, 8:30 a.m.-5 p.m.
Longitudinal studies follow individuals over time and repeatedly measure health status. This module will provide an overview of statistical methods for the analysis of longitudinal data.
A brief introduction to pre-post data will be followed by an in-depth discussion of regression-based methods such as generalized linear mixed-effects models and generalized estimating equations. Relevant theoretical background will be provided. Examples from randomized controlled trials and observational studies will be used to illustrate key approaches and modeling strategies. Illustrative examples will be presented with R and STATA.
This course is targeted toward individuals with little or no prior exposure to statistical methods for longitudinal data analysis. Attendees interested in more experience applying these methods should also consider Module 6: Case Studies in Longitudinal Data Analysis.
Access 2017 Course Materials (2018 materials will be uploaded to this page prior to the start of the module)