AISM 53, 708-729
© 2001 ISM

A bootstrap approach to nonparametric regression for right censored data

Gang Li1 and Somnath Datta2

1Department of Biostatistics, School of Public Health, University of California, Los Angeles, CA 90095-1772, U.S.A.
2Department of Statistics, Franklin College of Arts and Sciences, University of Georgia, 204 Statistics Building, Athens, GA 30602-1952, U.S.A.,

(Received May 13, 1999; revised April 4, 2000)

Abstract.    In this paper a two-stage bootstrap method is proposed for nonparametric regression with right censored data. The method is applied to construct confidence intervals and bands for a conditional survival function. Its asymptotic validity is established using counting process techniques and martingale central limit theory. The performance of the bootstrap method is investigated in a Monte Carlo study. An illustration is given using a real data.

Key words and phrases:    Bootstrap, Beran's estimate, censoring, confidence bands, confidence intervals, Kaplan-Meier estimate, nonparametric regression, quantile regression.

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