The Conway-Maxwell-Poisson-generalized gamma regression model with long-term survivors

dc.contributorUniversidade de São Paulo (USP)
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-20T13:27:10Z
dc.date.available2014-05-20T13:27:10Z
dc.date.created2014-05-20T13:27:10Z
dc.date.issued2011-01-01
dc.identifierJournal of Statistical Computation and Simulation. Abingdon: Taylor & Francis Ltd, v. 81, n. 11, p. 1461-1481, 2011.
dc.identifier0094-9655
dc.identifierhttp://hdl.handle.net/11449/8861
dc.identifier10.1080/00949655.2010.491827
dc.identifierWOS:000299726700008
dc.identifier5267593860042306
dc.description.abstractIn this paper, we proposed a flexible cure rate survival model by assuming the number of competing causes of the event of interest following the Conway-Maxwell distribution and the time for the event to follow the generalized gamma distribution. This distribution can be used to model survival data when the hazard rate function is increasing, decreasing, bathtub and unimodal-shaped including some distributions commonly used in lifetime analysis as particular cases. Some appropriate matrices are derived in order to evaluate local influence on the estimates of the parameters by considering different perturbations, and some global influence measurements are also investigated. Finally, data set from the medical area is analysed.
dc.languageeng
dc.publisherTaylor & Francis Ltd
dc.relationJournal of Statistical Computation and Simulation
dc.relation0.869
dc.relation0,704
dc.rightsAcesso restrito
dc.sourceWeb of Science
dc.subjectCOM-Poisson distributions
dc.subjectcure fraction models
dc.subjectgeneralized gamma distributions
dc.subjectsensitivity analysis
dc.subjectlifetime data
dc.titleThe Conway-Maxwell-Poisson-generalized gamma regression model with long-term survivors
dc.typeArtículos de revistas


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