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Activity Number: 17
Type: Topic Contributed
Date/Time: Sunday, August 3, 2008 : 2:00 PM to 3:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #301703
Title: Comparisons of Rank-Based Estimators for GEE Models
Author(s): Joseph McKean*+ and Ash Abebe and John Kloke
Companies: Western Michigan University and Auburn University and Pomona College
Address: , , 49008,
Keywords: Diagnostics ; Iterated reweighted least squares ; Monte Carlo ; Nonparametric ; Wilcoxon
Abstract:

Several recently proposed rank-based estimators of the effects in a GEE model are discussed. One of these estimators is based on an iterated reweighted least squares estimator for general linear and nonlinear models and another is based on a generalized R estimator. For both, weights can be chosen to bound influence in both the response and factor spaces. Illustrative examples and results of small sample investigations of this estimator and several other R estimators (which have optimal properties for specific GEE designs), are presented. Where appropriate, robust variance component estimators and related diagnostic procedures are also discussed.

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