Abstract #300396

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JSM 2003 Abstract #300396
Activity Number: 111
Type: Topic Contributed
Date/Time: Monday, August 4, 2003 : 10:30 AM to 12:20 PM
Sponsor: ENAR
Abstract - #300396
Title: Robustness Issues for Estimating Equation Methods
Author(s): Peiyong (Annie) Qu*+
Companies: Oregon State University
Address: Dept. of Statistics, Corvallis, OR, 97331-8553,
Keywords: contaminations ; generalized estimating equation ; generalized method of moments ; outliers ; quadratic inference function
Abstract:

We investigate the performance of the generalized method of moments (GMM) estimator on consistency when introducing outlier or contaminated observations. Our findings show that the GMM estimator is consistent if the number of contaminated subjects is no greater than the difference between numbers of moment conditions and parameters, and other nonrestricted conditions are satisfied. This implies that the quadratic inference function estimator under generalized estimating equation (GEE) settings is more robust against outliers than the GEE estimator since the former approach has more moment conditions than unknown parameters. Simulations and real data examples will be provided as illustrations. This is joint work with David Birks.

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