Cox survival models with partially crossed random effects: A Poisson modelling approach

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dc.contributor.advisorMa, Renjun
dc.contributor.advisorYan, Guohua
dc.contributor.authorZhang, Shi
dc.date.accessioned2023-10-17T14:35:46Z
dc.date.available2023-10-17T14:35:46Z
dc.date.issued2022-11
dc.description.abstractIn automobile insurance studies, the time to settlement data are often partially cross-classified by location and agent. Our research question of great interest is to link time to settlement with various covariates since the analysis information help develop procedures to detect fraud and process claims. An appropriate analysis of such data needs to account for location and agent effects. In this thesis, we incorporate partially crossed random effects into Cox survival models for such data and propose a Poisson modelling approach to model estimation. We predict the random effects using the orthodox best linear unbiased predictor method, and obtain consistent estimators for the regression parameters. This estimating method relies on only the first and second moments of the random effects, and is thus robust against distributional assumptions of random effects. The usefulness of our approach is demonstrated by simulation and application to the time to settlement data.
dc.description.copyright© Shi Zhang, 2022
dc.format.extentix, 61
dc.format.mediumelectronic
dc.identifier.oclc(OCoLC)1419274548en
dc.identifier.otherThesis 11198en
dc.identifier.urihttps://unbscholar.lib.unb.ca/handle/1882/37489
dc.language.isoen
dc.publisherUniversity of New Brunswick
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subject.disciplineMathematics and Statistics
dc.subject.lcshAutomobile insurance.en
dc.subject.lcshPoisson processes.en
dc.subject.lcshAutomobile insurance policies.en
dc.subject.lcshInsurance claims.en
dc.titleCox survival models with partially crossed random effects: A Poisson modelling approach
dc.typemaster thesis
oaire.license.conditionother
thesis.degree.disciplineMathematics and Statistics
thesis.degree.grantorUniversity of New Brunswick
thesis.degree.levelmasters
thesis.degree.nameM.Sc.

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