Poisson cure rate model with generalized exponential lifetimes

dc.contributor.authorSiddiqua, Joynob Ara
dc.contributor.examiningcommitteeBalakrishnan, N. (Mathematics and Statistics, McMaster University); Muthukumarana, Saman (Statistics)en_US
dc.contributor.supervisorDavies, Katherine (Statistics)en_US
dc.date.accessioned2018-07-30T20:40:36Z
dc.date.available2018-07-30T20:40:36Z
dc.date.issued2018-05-16en_US
dc.date.submitted2018-05-17T00:22:07Zen
dc.degree.disciplineStatisticsen_US
dc.degree.levelMaster of Science (M.Sc.)en_US
dc.description.abstractIn this thesis, we consider a competing risks scenario wherein lifetimes are potentially right censored. Instead of considering all the patients to be at risk to the event of interest, we assume that a proportion of these patients are cured and have no recurrence of the disease, known as the cure fraction. We further assume that the number of competing risks is random and follows a Poisson distribution. We consider the lifetimes of individuals to follow a two parameter generalized exponential distribution. The objective is to estimate the model parameters. Using a direct approach and the expectation maximization estimation approach, we obtain maximum likelihood estimates. Standard errors of the estimates are obtained by inverting the observed Fisher information matrix. Monte Carlo simulations are used to demonstrate the performance of the two methods of estimation. Finally, we fit our model to two real data sets to illustrate the model competence.en_US
dc.description.noteOctober 2018en_US
dc.identifier.urihttp://hdl.handle.net/1993/33185
dc.language.isoengen_US
dc.rightsopen accessen_US
dc.subjectcure rate, generalized exponential distribution, lifetimes, competing risks, censoring, Poisson distributionen_US
dc.titlePoisson cure rate model with generalized exponential lifetimesen_US
dc.typemaster thesisen_US
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