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Comparison on modelling the relative risk estimation: Bayesian study

The estimation of the disease incidents was previously analyzed using a classical approach. However, this approach features large outlying relative risks and considered as misleading due to several major problems. Some approaches such as the hierarchical Bayesian method have been adopted in the lite...

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Main Authors: M. Elobaid, Rafida, Ibrahim, Noor Akma
Format: Article
Language:English
Published: Hikari Ltd. 2010
Online Access:http://psasir.upm.edu.my/id/eprint/13710/1/Comparison%20on%20modelling%20the%20relative%20risk%20estimation.pdf
http://psasir.upm.edu.my/id/eprint/13710/
http://www.m-hikari.com/ams/ams-2010/ams-53-56-2010/index.html
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spelling my.upm.eprints.137102015-10-21T00:12:05Z http://psasir.upm.edu.my/id/eprint/13710/ Comparison on modelling the relative risk estimation: Bayesian study M. Elobaid, Rafida Ibrahim, Noor Akma The estimation of the disease incidents was previously analyzed using a classical approach. However, this approach features large outlying relative risks and considered as misleading due to several major problems. Some approaches such as the hierarchical Bayesian method have been adopted in the literature in order to overcome these problems. The purpose of this study is to compare between hierarchical Bayesian models that improve the relative risk estimation. The focus lies on examining the performance of different sets of densities via monitoring the history graphs, estimating the potential scale reduction factors and conducting sensitivity analysis for different choice of prior information. The best model fit is accomplished by conducting a goodness of fit test. The study is applied on Scotland lip cancer data set. The results show that for models with large number of parameters, more iteration is needed to achieve the convergence. The study also shows that diagnostic test and sensitivity analysis are important to decide about the stability and the the influence of the choice of the prior densities. The DIC results were in line with the previous results and provide a good method of comparison. Hikari Ltd. 2010 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/13710/1/Comparison%20on%20modelling%20the%20relative%20risk%20estimation.pdf M. Elobaid, Rafida and Ibrahim, Noor Akma (2010) Comparison on modelling the relative risk estimation: Bayesian study. Applied Mathematical Sciences, 4 (53-56). pp. 2663-2681. ISSN 1312-885X; ESSN: 1314-7552 http://www.m-hikari.com/ams/ams-2010/ams-53-56-2010/index.html
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description The estimation of the disease incidents was previously analyzed using a classical approach. However, this approach features large outlying relative risks and considered as misleading due to several major problems. Some approaches such as the hierarchical Bayesian method have been adopted in the literature in order to overcome these problems. The purpose of this study is to compare between hierarchical Bayesian models that improve the relative risk estimation. The focus lies on examining the performance of different sets of densities via monitoring the history graphs, estimating the potential scale reduction factors and conducting sensitivity analysis for different choice of prior information. The best model fit is accomplished by conducting a goodness of fit test. The study is applied on Scotland lip cancer data set. The results show that for models with large number of parameters, more iteration is needed to achieve the convergence. The study also shows that diagnostic test and sensitivity analysis are important to decide about the stability and the the influence of the choice of the prior densities. The DIC results were in line with the previous results and provide a good method of comparison.
format Article
author M. Elobaid, Rafida
Ibrahim, Noor Akma
spellingShingle M. Elobaid, Rafida
Ibrahim, Noor Akma
Comparison on modelling the relative risk estimation: Bayesian study
author_facet M. Elobaid, Rafida
Ibrahim, Noor Akma
author_sort M. Elobaid, Rafida
title Comparison on modelling the relative risk estimation: Bayesian study
title_short Comparison on modelling the relative risk estimation: Bayesian study
title_full Comparison on modelling the relative risk estimation: Bayesian study
title_fullStr Comparison on modelling the relative risk estimation: Bayesian study
title_full_unstemmed Comparison on modelling the relative risk estimation: Bayesian study
title_sort comparison on modelling the relative risk estimation: bayesian study
publisher Hikari Ltd.
publishDate 2010
url http://psasir.upm.edu.my/id/eprint/13710/1/Comparison%20on%20modelling%20the%20relative%20risk%20estimation.pdf
http://psasir.upm.edu.my/id/eprint/13710/
http://www.m-hikari.com/ams/ams-2010/ams-53-56-2010/index.html
_version_ 1643825412151705600
score 13.211869

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