Bayesian survival analysis using gene expression

(2013) Bayesian survival analysis using gene expression. PhD by Publication, Queensland University of Technology.

Description

This thesis developed and applied Bayesian models for the analysis of survival data. The gene expression was considered as explanatory variables within the Bayesian survival model which can be considered the new contribution in the analysis of such data. The censoring factor that is inherent of survival data has also been addressed in terms of its impact on the fitting of a finite mixture of Weibull distribution with and without covariates. To investigate this, simulation study were carried out under several censoring percentages. Censoring percentage as high as 80% is acceptable here as the work involved high dimensional data. Lastly the Bayesian model averaging approach was developed to incorporate model uncertainty in the prediction of survival.

Impact and interest:

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3,055 since deposited on 23 Sep 2013
24 in the past twelve months

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ID Code: 62666
Item Type: QUT Thesis (PhD by Publication)
Supervisor: Mengersen, Kerrie & McGree, James
Keywords: Bayesian Modelling, Survival Analysis, Weibull Distribution, Bayesian Model Averaging, Gene Expression
Divisions: Past > QUT Faculties & Divisions > Science & Engineering Faculty
Current > Schools > School of Mathematical Sciences
Institution: Queensland University of Technology
Deposited On: 23 Sep 2013 03:22
Last Modified: 05 Sep 2017 14:41