Online Program Home
My Program

Abstract Details

Activity Number: 212630
Type: Professional Development
Date/Time: Saturday, July 30, 2016 : 8:30 AM to 5:00 PM
Sponsor: Biometrics Section
Abstract #321862
Title: Applied Longitudinal Analysis (ADDED FEE)
Author(s): Garrett Fitzmaurice *
Companies: Harvard T.H. Chan School of Public Health

The goal of this course is to provide a broad introduction to statistical methods for analyzing longitudinal data. The emphasis is on the practical aspects of longitudinal analysis. The course begins with a review of established methods for longitudinal data analysis when the response of interest is continuous. A general introduction to linear mixed effects models for continuous responses is presented. Next, we discuss how smoothing and semiparametric regression allow greater flexibility for the form of the relationship between the mean response and covariates. We demonstrate how the mixed model representation of penalized splines makes this extension straightforward. When the response of interest is categorical (e.g., binary or count data), two main extensions of generalized linear models to longitudinal data have been proposed: marginal models and generalized linear mixed models. While both classes of models account for the within-subject correlation among the repeated measures, they differ in approach. In this course, we highlight the main distinctions between these models and discuss the types of scientific questions addressed by each.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2016 program

Copyright © American Statistical Association