Bootstrapping the conditional survival function estimator in the partial Koziol-Green model

In the partial Koziol-Green regression model, the lifetime variable may be censored by two types of censoring variables. One is called informative because it satisfies the Koziol-Green assumption on proportionality of hazards and the other one is general. Braekers and Veraverbeke proposed a non-para...

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Published in:Journal of nonparametric statistics 2005-04, Vol.17 (3), p.299-318
Main Authors: Braekers, Roel, Veraverbeke, Noël
Format: Article
Language:English
Subjects:
Bootstrap
Fixed design
Informative censoring
Nonparametric regression
Proportional hazards
Right censoring
Weak convergence
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description In the partial Koziol-Green regression model, the lifetime variable may be censored by two types of censoring variables. One is called informative because it satisfies the Koziol-Green assumption on proportionality of hazards and the other one is general. Braekers and Veraverbeke proposed a non-parametric estimator for the conditional lifetime distribution and obtained a Gaussian approximation for the corresponding process. In the present paper, we propose an appropriate resampling scheme and show that this leads to a valid bootstrap approximation for the process.
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subjects Bootstrap
Fixed design
Informative censoring
Nonparametric regression
Proportional hazards
Right censoring
Weak convergence
title Bootstrapping the conditional survival function estimator in the partial Koziol-Green model
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