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Activity Number: 481
Type: Contributed
Date/Time: Wednesday, August 9, 2006 : 2:00 PM to 3:50 PM
Sponsor: General Methodology
Abstract - #305766
Title: Large-Cluster Asymptotics for GEE: Working Correlation Models
Author(s): Hyoju Chung*+ and Thomas Lumley
Companies: University of Washington and University of Washington
Address: Box 357232, Seattle, WA, 98195-7232,
Keywords: generalized estimating equations ; working correlation model ; empirical process theory
Abstract:

We consider generalized estimating equations models for correlated data and present large cluster asymptotics. The complexity of working correlation models, which is characterized in terms of the dimension of working correlation parameter, may increase with the number of independent clusters. In our two-index asymptotic setting we show the existence, weak consistency and asymptotic normality of marginal regression parameter estimators using results of empirical process theory. We present sufficient conditions for the increasing complexity of working correlation models using maximal inequalities.

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