A comparative study of maximum likelihood and bayesian estimation approaches in estimating of gamma frailty mixture survival model parameters

Frailty mixture survival models are survival models that allow for a cured fraction and frailty at the same time. This study applies Gamma frailty mixture survival model on time-to-recurrence data of leukaemia patients who received an autologous treatment. The model involves 4 unknown parameters inc...

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Main Author:	Oh, Yit Leng
Format:	Thesis
Published:	2010
Subjects:	Q Science (General)
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id	my-utm-ep.16327
record_format	uketd_dc
spelling	my-utm-ep.163272017-07-31T06:37:48Z A comparative study of maximum likelihood and bayesian estimation approaches in estimating of gamma frailty mixture survival model parameters 2010 Oh, Yit Leng Q Science (General) Frailty mixture survival models are survival models that allow for a cured fraction and frailty at the same time. This study applies Gamma frailty mixture survival model on time-to-recurrence data of leukaemia patients who received an autologous treatment. The model involves 4 unknown parameters including the long-term survivor parameter. The choice of estimation approaches is important, since the estimation of parameters will influent the accuracy and performance of the survival model. The estimation approaches that are often used in survival analysis are Maximum Likelihood (ML) and Bayesian estimation approaches. The study aims to compare the performance of Maximum Likelihood (ML) and Bayesian estimators of Gamma frailty mixture survival model in terms of their accuracy and efficiency by comparing their mean square error (MSE) and model fits using goodness of fit test. This study found that maximum likelihood estimators perform better than Bayesian estimators in obtaining the parameter of Gamma frailty mixture survival model of this study. 2010 Thesis http://eprints.utm.my/id/eprint/16327/ masters Universiti Teknologi Malaysia, Faculty of Science Faculty of Science
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
topic	Q Science (General)
spellingShingle	Q Science (General) Oh, Yit Leng A comparative study of maximum likelihood and bayesian estimation approaches in estimating of gamma frailty mixture survival model parameters
description	Frailty mixture survival models are survival models that allow for a cured fraction and frailty at the same time. This study applies Gamma frailty mixture survival model on time-to-recurrence data of leukaemia patients who received an autologous treatment. The model involves 4 unknown parameters including the long-term survivor parameter. The choice of estimation approaches is important, since the estimation of parameters will influent the accuracy and performance of the survival model. The estimation approaches that are often used in survival analysis are Maximum Likelihood (ML) and Bayesian estimation approaches. The study aims to compare the performance of Maximum Likelihood (ML) and Bayesian estimators of Gamma frailty mixture survival model in terms of their accuracy and efficiency by comparing their mean square error (MSE) and model fits using goodness of fit test. This study found that maximum likelihood estimators perform better than Bayesian estimators in obtaining the parameter of Gamma frailty mixture survival model of this study.
format	Thesis
qualification_level	Master's degree
author	Oh, Yit Leng
author_facet	Oh, Yit Leng
author_sort	Oh, Yit Leng
title	A comparative study of maximum likelihood and bayesian estimation approaches in estimating of gamma frailty mixture survival model parameters
title_short	A comparative study of maximum likelihood and bayesian estimation approaches in estimating of gamma frailty mixture survival model parameters
title_full	A comparative study of maximum likelihood and bayesian estimation approaches in estimating of gamma frailty mixture survival model parameters
title_fullStr	A comparative study of maximum likelihood and bayesian estimation approaches in estimating of gamma frailty mixture survival model parameters
title_full_unstemmed	A comparative study of maximum likelihood and bayesian estimation approaches in estimating of gamma frailty mixture survival model parameters
title_sort	comparative study of maximum likelihood and bayesian estimation approaches in estimating of gamma frailty mixture survival model parameters
granting_institution	Universiti Teknologi Malaysia, Faculty of Science
granting_department	Faculty of Science
publishDate	2010
_version_	1747815016653914112

A comparative study of maximum likelihood and bayesian estimation approaches in estimating of gamma frailty mixture survival model parameters

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