Abstract #300372

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JSM 2003 Abstract #300372
Activity Number: 111
Type: Topic Contributed
Date/Time: Monday, August 4, 2003 : 10:30 AM to 12:20 PM
Sponsor: ENAR
Abstract - #300372
Title: Combining Between-Cluster and Within-Cluster Estimates
Author(s): Julie A. Stoner*+ and Brian G. Leroux
Companies: University of Nebraska and University of Washington
Address: Preventive and Societal Medicine, Omaha, NE, 68198-4350,
Keywords: between-cluster estimate ; correlated data ; generalized estimating equations ; within-cluster estimate
Abstract:

Correlated data, arising from longitudinal studies or cluster sampling studies, provide multiple sources of information regarding covariate effects in a marginal regression setting. For example, between-cluster and within-cluster contrasts may both provide information about the effect of interest. Generalized estimating equations (GEE) weight and combine such sources of information in a particular manner depending on the working correlation structure, which may not be optimal depending on the agreement between the true and working correlation structures. We have developed a marginal regression method that optimally weights and combines between-cluster and within-cluster information in a correlated data setting through a combination of estimating equations. The combination of estimating equations approach will be described and compared to a method based on a combination of estimates from GEE models using standard software. Efficiency gains, relative to GEE with standard working correlation structures, will be presented through simulations and an example in periodontal research will be discussed.

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