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Activity Number: 702
Type: Contributed
Date/Time: Thursday, August 13, 2015 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract #315031 View Presentation
Title: Choosing a Working Correlation Structure for GEE: Making Use of Selection Penalties
Author(s): Philip Westgate* and Woodrow Burchett
Companies: University of Kentucky and University of Kentucky
Keywords: Correlation ; Efficiency ; Generalized Estimating Equations ; Longitudinal Data
Abstract:

Generalized estimating equations (GEE) are frequently used for the marginal analysis of correlated data. With GEE, a working correlation structure must be selected. Accurate modeling of this structure can improve the efficiency of regression parameter estimation, although estimating nuisance correlation parameters can have the opposite impact. We therefore discuss and contrast different ways to penalize, or account for, correlation parameter estimation, with the goal of improving regression parameter estimation. Our focus will be on the use of GEE for the analysis of longitudinal data.


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

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