Bootstrap intervals in the presence of left-truncation, censoring and covariates with a parametric distribution

Left-truncated and censored survival data are commonly encountered in medical studies. However, traditional inferential methods that heavily rely on normality assumptions often fail when lifetimes of observations in a study are both truncated and censored. Thus, it is important to develop alternativ...

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Main Authors: Thirunanthini Manoharan, Jayanthi Arasan, Habshah Midi, Mohd Bakri Adam
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2017
Online Access:http://journalarticle.ukm.my/11723/
http://journalarticle.ukm.my/11723/1/31%20Thirunanthini.pdf
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author Thirunanthini Manoharan,
Jayanthi Arasan,
Habshah Midi,
Mohd Bakri Adam,
author_facet Thirunanthini Manoharan,
Jayanthi Arasan,
Habshah Midi,
Mohd Bakri Adam,
author_sort Thirunanthini Manoharan,
building UKM Institutional Repository
collection Online Access
description Left-truncated and censored survival data are commonly encountered in medical studies. However, traditional inferential methods that heavily rely on normality assumptions often fail when lifetimes of observations in a study are both truncated and censored. Thus, it is important to develop alternative inferential procedures that ease the assumptions of normality and unconventionally relies on the distribution of data in hand. In this research, a three parameter log-normal parametric survival model was extended to incorporate left-truncated and right censored medical data with covariates. Following that, bootstrap inferential procedures using non-parametric and parametric bootstrap samples were applied to the parameters of this model. The performance of the parameter estimates was assessed at various combinations of truncation and censoring levels via a simulation study. The recommended bootstrap intervals were applied to a lung cancer survival data.
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spelling oai:generic.eprints.org:117232018-05-30T00:02:33Z http://journalarticle.ukm.my/11723/ Bootstrap intervals in the presence of left-truncation, censoring and covariates with a parametric distribution Thirunanthini Manoharan, Jayanthi Arasan, Habshah Midi, Mohd Bakri Adam, Left-truncated and censored survival data are commonly encountered in medical studies. However, traditional inferential methods that heavily rely on normality assumptions often fail when lifetimes of observations in a study are both truncated and censored. Thus, it is important to develop alternative inferential procedures that ease the assumptions of normality and unconventionally relies on the distribution of data in hand. In this research, a three parameter log-normal parametric survival model was extended to incorporate left-truncated and right censored medical data with covariates. Following that, bootstrap inferential procedures using non-parametric and parametric bootstrap samples were applied to the parameters of this model. The performance of the parameter estimates was assessed at various combinations of truncation and censoring levels via a simulation study. The recommended bootstrap intervals were applied to a lung cancer survival data. Penerbit Universiti Kebangsaan Malaysia 2017-12 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/11723/1/31%20Thirunanthini.pdf Thirunanthini Manoharan, and Jayanthi Arasan, and Habshah Midi, and Mohd Bakri Adam, (2017) Bootstrap intervals in the presence of left-truncation, censoring and covariates with a parametric distribution. Sains Malaysiana, 46 (12). pp. 2529-2539. ISSN 0126-6039 http://www.ukm.my/jsm/english_journals/vol46num12_2017/contentsVol46num12_2017.htm
spellingShingle Thirunanthini Manoharan,
Jayanthi Arasan,
Habshah Midi,
Mohd Bakri Adam,
Bootstrap intervals in the presence of left-truncation, censoring and covariates with a parametric distribution
title Bootstrap intervals in the presence of left-truncation, censoring and covariates with a parametric distribution
title_full Bootstrap intervals in the presence of left-truncation, censoring and covariates with a parametric distribution
title_fullStr Bootstrap intervals in the presence of left-truncation, censoring and covariates with a parametric distribution
title_full_unstemmed Bootstrap intervals in the presence of left-truncation, censoring and covariates with a parametric distribution
title_short Bootstrap intervals in the presence of left-truncation, censoring and covariates with a parametric distribution
title_sort bootstrap intervals in the presence of left-truncation, censoring and covariates with a parametric distribution
url http://journalarticle.ukm.my/11723/
http://journalarticle.ukm.my/11723/
http://journalarticle.ukm.my/11723/1/31%20Thirunanthini.pdf