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Joint Statistics / Biostatistics and Medical Informatics Seminar


Inference based on estimating functions
with U-Statistic structure

Jack Kalbfleisch, PhD
Professor and Chair, Department of Biostatistics, University of Michigan

Wednesday, April 14, 2004, 4-5 p.m.

1221 Computer Sciences and Statistics building, 1210 West Dayton St.


Suppose that inference about parameters of interest is to be based on an unbiased estimating function that is a U-statistic of degree 1 or 2. We define suitable studentized versions of such estimating functions and consider asymptotic approximations as well as an estimating function bootstrap (EFB) method based on resampling the estimated terms in the estimating function. These methods are justified asymptotically and lead to confidence intervals produced directly from the studentized estimating function. Particular examples in this class of problems include La estimation as well as Wilcoxon rank regression and other related estimation problems. The proposed methods are evaluated in examples and simulations and compared with a recent suggestion for inference in such problems which relies on resampling an underlying objective function (Jin, Ying and Wei, 2001, Biometrika).


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