Nonparametric likelihood ratio confidence bands for quantile functions from incomplete survival data
Myles Hollander, Ian W. McKeague, Jie Yang, and Gang Li
Source: Ann. Statist. Volume 24, Number 2
(1996), 628-640.
Abstract
The purpose of this paper is to derive confidence bands for quantile functions using a nonparametric likelihood ratio approach. The method is easy to implement and has several appealing properties. It applies to right-censored and left-truncated data, and it does not involve density estimation or even require the existence of a density. Previous approaches (e.g., bootstrap) have imposed smoothness conditions on the density. The performance of the proposed method is investigated in a Monte Carlo study, and an application to real data is given.
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Keywords: Empirical likelihood; Hall-Wellner band; Kaplan-Meier estimator; multiplicative intensity model; censoring; truncation
Full-text: Open access
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Permanent link to this document: http://projecteuclid.org/euclid.aos/1032894455
Mathematical Reviews number (MathSciNet): MR1394978
Digital Object Identifier: doi:10.1214/aos/1032894455
Zentralblatt MATH identifier: 0859.62047
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CHARLOTTE, NORTH CAROLINA 28223 DEPARTMENT OF STATISTICS FLORIDA STATE UNIVERSITY
TALLAHASSEE, FLORIDA 32306
