This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 87
Type: Contributed
Date/Time: Sunday, August 1, 2010 : 4:00 PM to 5:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #306492
Title: Modified Robust Covariance Estimator for Generalized Estimating Equations with Improved Small-Sample Properties
Author(s): Ming Wang*+ and Qi Long
Companies: Emory University and Emory University
Address: 1536 Druid Oaks NE, Atlanta, GA, 30329,
Keywords: Generalized estimating equations ; Sandwich covariance estimator ; Longitudinal data ; Small sample size ; Mixed-effect model
Abstract:

Generalized Estimating Equations(GEE, 1998) is a general statistical method to fit marginal models for correlated responses.It uses a robust sandwich estimator to estimate the covariance of the regression coefficient estimates; however, its finite sample performance deteriorates as the sample size decreases.To address this limitation, Pan(2001) and Mancl and DeRouen(2001) provided two modifications.Motivated by their ideas, we propose a novel robust variance estimator that combines the strength of both estimators.Our theoretical and numerical results show that the proposed estimator achieves better finite sample performance and efficiency.In particular, when the sample size is small, our proposal exhibits substantially lower bias,and the confidence intervals for GEE estimates using our proposal attain considerably better coverage properties.The methods are illustrated with a dental data.


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