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Activity Number: 149
Type: Contributed
Date/Time: Monday, July 30, 2007 : 10:30 AM to 12:20 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #309428
Title: Diagnostics for Rank Estimates for a Mixed Model
Author(s): John Kloke*+ and Joseph W. McKean and M. Mushfiqur Rashid
Companies: Pomona College and Western Michigan University and Food and Drug Administration
Address: , Claremont, CA, 91711,
Keywords:
Abstract:

Jurevckova (1971) and Jaeckel (1972) developed asymptotic theory for iid linear models. Ordinary rank (OR) estimators are those which minimize Jaeckel's dispersion function. Theory for OR estimators for certain mixed models follows in a manner similar to that of the iid case. We briefly discuss these asymptotic results. The majority of the talk, however, will be devoted to discussing diagnostic procedures for these models (e.g., studentized residuals). References: Jaeckel, L. A. (1972), Estimating regression coefficients by minimizing the dispersion of the residuals, Annals of Mathematical Statistics, 43, 1449--1458. Jurevckova, J. (1971), Nonparametric estimate of regression coefficients, Annals of Mathematical Statistics, 42, 1328--1338.

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Revised September, 2007