A Bayesian Poisson mixed modelling approach to survival model with compound Poisson distributed frailty

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dc.contributor.advisorYan, Guohua
dc.contributor.advisorRenjun Ma
dc.contributor.authorYu, Qing
dc.date.accessioned2023-03-01T16:18:26Z
dc.date.available2023-03-01T16:18:26Z
dc.date.issued2016
dc.date.updated2023-03-01T15:01:28Z
dc.description.abstractIn survival studies, a subgroup of subjects may have zero susceptibility to the event of interest. For example, some people may be immune to a certain disease. These kind of data occur widely in medicine, social science and environment studies. The frailties therefore consist of a mix of zero and positive values. This poses some challenges in data analysis as there is no standard distribution for the frailties. Our work is motivated by Ma et al. (2003 & 2009). They have presented a multilevel frailties Poisson model for the survival data. In this thesis, we propose a Bayesian mixed model for survival data with zero-inflated frailties. With our approach, the zero and positive frailties are modeled using a compound Poisson distribution in an integral manner. We use the Markov chain Monte Carlo algorithm (MCMC) and the Bayesian approach to estimate the regression parameters and the frailties. Two data sets, jail time data and third birth data, are used to illustrate our proposed method.
dc.description.copyright© Qing Yu, 2016
dc.formattext/xml
dc.format.extentix, 64 pages
dc.format.mediumelectronic
dc.identifier.urihttps://unbscholar.lib.unb.ca/handle/1882/13425
dc.language.isoen_CA
dc.publisherUniversity of New Brunswick
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subject.disciplineMathematics and Statistics
dc.titleA Bayesian Poisson mixed modelling approach to survival model with compound Poisson distributed frailty
dc.typemaster thesis
thesis.degree.disciplineMathematics and Statistics
thesis.degree.fullnameMaster of Science
thesis.degree.grantorUniversity of New Brunswick
thesis.degree.levelmasters
thesis.degree.nameM.Sc.

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