Jackknife and bootstrap inferential procedures for censored survival data
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...
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AIP Publishing LLC
2014
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my.upm.eprints.573372017-09-26T04:07:04Z http://psasir.upm.edu.my/id/eprint/57337/ Jackknife and bootstrap inferential procedures for censored survival data Loh, Yue Fang Arasan, Jayanthi Midi, Habshah Abu Bakar, Mohd Rizam 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. AIP Publishing LLC 2014 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/57337/1/Jackknife%20and%20bootstrap%20inferential%20procedures%20for%20censored%20survival%20data.pdf 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). 10.1063/1.4934631 |
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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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Conference or Workshop Item |
author |
Loh, Yue Fang Arasan, Jayanthi Midi, Habshah Abu Bakar, Mohd Rizam |
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Loh, Yue Fang Arasan, Jayanthi Midi, Habshah Abu Bakar, Mohd Rizam Jackknife and bootstrap inferential procedures for censored survival data |
author_facet |
Loh, Yue Fang Arasan, Jayanthi Midi, Habshah Abu Bakar, Mohd Rizam |
author_sort |
Loh, Yue Fang |
title |
Jackknife and bootstrap inferential procedures for censored survival data |
title_short |
Jackknife and bootstrap inferential procedures for censored survival data |
title_full |
Jackknife and bootstrap inferential procedures for censored survival data |
title_fullStr |
Jackknife and bootstrap inferential procedures for censored survival data |
title_full_unstemmed |
Jackknife and bootstrap inferential procedures for censored survival data |
title_sort |
jackknife and bootstrap inferential procedures for censored survival data |
publisher |
AIP Publishing LLC |
publishDate |
2014 |
url |
http://psasir.upm.edu.my/id/eprint/57337/1/Jackknife%20and%20bootstrap%20inferential%20procedures%20for%20censored%20survival%20data.pdf http://psasir.upm.edu.my/id/eprint/57337/ |
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