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Smoothed Bootstrap for Right-Censored Data

Luhayb, Asamh Saleh M. Al; Coolen, Frank P.A.; Coolen-Maturi, Tahani

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Authors

Asamh Saleh M. Al Luhayb



Abstract

A smoothed bootstrap method is introduced for right-censored data based on the right-censoring-A(n) assumption introduced by Coolen and Yan, which is a generalization of Hill’s A(n) assumption for right-censored data. The smoothed bootstrap method is compared to Efron’s method for right-censored data through simulations. The comparison is conducted in terms of the coverage of percentile confidence intervals for the quartiles. From the study, it is found that the smoothed bootstrap method mostly performs better than Efron’s method, in particular for small data sets. We also illustrate the use of the method for survival function inference and compare it to a smoothed Kaplan-Meier bootstrap method through simulations.

Citation

Luhayb, A. S. M. A., Coolen, F. P., & Coolen-Maturi, T. (2023). Smoothed Bootstrap for Right-Censored Data. Communications in Statistics - Theory and Methods, https://doi.org/10.1080/03610926.2023.2171708

Journal Article Type Article
Acceptance Date Jan 1, 2023
Online Publication Date Jan 27, 2023
Publication Date Jan 27, 2023
Deposit Date Nov 21, 2022
Publicly Available Date Jan 28, 2024
Journal Communications in Statistics - Theory and Methods
Print ISSN 0361-0926
Electronic ISSN 1532-415X
Publisher Taylor and Francis Group
Peer Reviewed Peer Reviewed
DOI https://doi.org/10.1080/03610926.2023.2171708
Public URL https://durham-repository.worktribe.com/output/1188503

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