Estimation of the Base Hazard Function by Bootstrapping

This thesis examines the techniques in estimating the base hazard function by bootstrapping. The base hazard function is a crucial part of survival analysis. It is used to construct an estimate of the proportional hazard model for every individual. As in many methods for analysing survival data,...

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Main Author: Arlin, Rifina
Format: Thesis
Language:English
English
Published: 2004
Subjects:
Online Access:http://psasir.upm.edu.my/id/eprint/30/1/1000548962_t_FS_2004_2.pdf
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author Arlin, Rifina
author_facet Arlin, Rifina
author_sort Arlin, Rifina
collection UPM
description This thesis examines the techniques in estimating the base hazard function by bootstrapping. The base hazard function is a crucial part of survival analysis. It is used to construct an estimate of the proportional hazard model for every individual. As in many methods for analysing survival data, this thesis utilizes the nonparametric model of Kaplan Meier, the Cox proportional hazard regression of the parametric model and the data validation by bootstrapping. The Cox proportional hazard regression is used to model failure time data in censored data. Bootstrapping schemes validate the models based on Efron’s technique and the data samples are generated using S-Plus programme randomizer. v Assessment of this method is investigated by performing simulation study on generated data. Two simulation studies are carried out to confirm the suitability of the models. Graph obtained from the results indicated that bootstrapping provides an alternative method in constructing estimation for base hazard function. This method is good alternative for a distribution-free approach with a minimal set of data.
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spelling upm.eprints-302013-05-27T06:45:08Z http://psasir.upm.edu.my/id/eprint/30/ Estimation of the Base Hazard Function by Bootstrapping Arlin, Rifina This thesis examines the techniques in estimating the base hazard function by bootstrapping. The base hazard function is a crucial part of survival analysis. It is used to construct an estimate of the proportional hazard model for every individual. As in many methods for analysing survival data, this thesis utilizes the nonparametric model of Kaplan Meier, the Cox proportional hazard regression of the parametric model and the data validation by bootstrapping. The Cox proportional hazard regression is used to model failure time data in censored data. Bootstrapping schemes validate the models based on Efron’s technique and the data samples are generated using S-Plus programme randomizer. v Assessment of this method is investigated by performing simulation study on generated data. Two simulation studies are carried out to confirm the suitability of the models. Graph obtained from the results indicated that bootstrapping provides an alternative method in constructing estimation for base hazard function. This method is good alternative for a distribution-free approach with a minimal set of data. 2004-12 Thesis NonPeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/30/1/1000548962_t_FS_2004_2.pdf Arlin, Rifina (2004) Estimation of the Base Hazard Function by Bootstrapping. Masters thesis, Universiti Putra Malaysia. Bootstrap (Statistics) English
spellingShingle Bootstrap (Statistics)
Arlin, Rifina
Estimation of the Base Hazard Function by Bootstrapping
title Estimation of the Base Hazard Function by Bootstrapping
title_full Estimation of the Base Hazard Function by Bootstrapping
title_fullStr Estimation of the Base Hazard Function by Bootstrapping
title_full_unstemmed Estimation of the Base Hazard Function by Bootstrapping
title_short Estimation of the Base Hazard Function by Bootstrapping
title_sort estimation of the base hazard function by bootstrapping
topic Bootstrap (Statistics)
url http://psasir.upm.edu.my/id/eprint/30/1/1000548962_t_FS_2004_2.pdf
work_keys_str_mv AT arlinrifina estimationofthebasehazardfunctionbybootstrapping