Live sessions will be held 8:30-noon, PT (11:30-3 p.m. ET) each day. Pre-recorded lectures, downloadable presentations, data sets and other course materials will be posted prior to the start of the module.

Longitudinal studies follow individuals over time and repeatedly measure health status, which facilitates prospective ascertainment of exposures and incident outcomes, and identification of changes over time within individuals. Analyses of longitudinal data must account for the correlation that arises from collecting repeated measures on the same individuals over time.

This module will overview statistical methods for the analysis of longitudinal data, with a focus on regression-based methods such as generalized linear mixed-effects models and generalized estimating equations. Relevant theoretical background will be provided. An illustrative example (conducted in R) will be used to illustrate analysis approaches, modeling strategies, and interpretation of results. This course is targeted toward individuals with little or no prior experience with statistical methods for longitudinal data analysis; experience with linear and logistic regression would be useful.