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

Abstract Details

Activity Number: 631
Type: Contributed
Date/Time: Thursday, August 5, 2010 : 8:30 AM to 10:20 AM
Sponsor: Section on Nonparametric Statistics
Abstract - #308666
Title: A Comparison of Rank-Based Methods for Mixed Models
Author(s): John Kloke*+ and Joseph W. McKean and M. Mushqur Rashid
Companies: Bucknell University and Western Michigan University and FDA
Address: Department of Mathematics, Lewisburg, PA, 17837,
Keywords: Nonparametric ; Random effects ; Rank regression scores ; Robust ; Wilcoxon

In recent years several rank-based approaches for analyzing cluster correlated data have been developed. Among these are two procedures for estimating the fixed effects in a mixed model. One such procedure is based on the joint rankings of all the residuals (Jaeckel type). The inference for this procedure involves robust estimations of correlation due to the random effect. A second procedure is based on minimizing a sum of rank-based convex functions over the clusters. The rankings of residuals for this second procedure are performed with in each cluster (Friedman type). In this talk we first provide a brief overview of these methods. Next we present the results of a large simulation study.

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