Jackknife and bootstrap inferential procedures for censored survival data

Citation

Loh, Yue Fang and Arasan, Jayanthi and Midi, Habshah and Abu Bakar, Mohd Rizam (2014) Jackknife and bootstrap inferential procedures for censored survival data. In: 22nd National Symposium on Mathematical Sciences (SKSM22), 24-26 Nov. 2014, Grand Bluewave Hotel, Selangor. (pp. 1-6).

Abstract

Confidence interval is an estimate of a certain parameter. Classical construction of confidence interval based on asymptotic normality (Wald) often produces misleading inferences when dealing with censored data especially in small samples. Alternative techniques allow us to construct the confidence interval estimation without relying on this assumption. In this paper, we compare the performances of the jackknife and several bootstraps confidence interval estimates for the parameters of a log logistic model with censored data and covariate. We investigate their performances at two nominal error probability levels and several levels of censoring proportion. Conclusions were then drawn based on the results of the coverage probability study.

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Additional Metadata

Item Type:	Conference or Workshop Item (Paper)
Divisions:	Faculty of Science Institute for Mathematical Research
DOI Number:	https://doi.org/10.1063/1.4934631
Publisher:	AIP Publishing LLC
Keywords:	Bootstrap; Censored data; Confidence interval; Coverage probability; Log logistic
Depositing User:	Nabilah Mustapa
Date Deposited:	26 Sep 2017 04:07
Last Modified:	26 Sep 2017 04:07
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1063/1.4934631
URI:	http://psasir.upm.edu.my/id/eprint/57337
Statistic Details:	View Download Statistic

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