Smoothed Bootstrap for Right-Censored Data

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

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. (in press). 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
• 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