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Biostatistics Advance Access published online on October 8, 2007
Biostatistics, doi:10.1093/biostatistics/kxm034
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© The Author 2007. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.

Efficient resampling methods for nonsmooth estimating functions

Donglin Zeng and D. Y. Lin*

Department of Biostatistics, CB 7420, University of North Carolina, Chapel Hill, NC 27599-7420, USA lin{at}bios.unc.edu

* To whom correspondence should be addressed.

We propose a simple and general resampling strategy to estimate variances for parameter estimators derived from nonsmooth estimating functions. This approach applies to a wide variety of semiparametric and nonparametric problems in biostatistics. It does not require solving estimating equations and is thus much faster than the existing resampling procedures. Its usefulness is illustrated with heteroscedastic quantile regression and censored data rank regression. Numerical results based on simulated and real data are provided.

Keywords: Bootstrap; Censoring; Quantile regression; Rank regression; Robustness; Variance estimation

Received January 4, 2007; revised August 24, 2007; accepted for publication August 31, 2007.


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