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Frailty Models for Arbitrarily Censored and Truncated Data

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dc.contributor.author Huber-Carol, C en
dc.contributor.author Vonta, I en
dc.date.accessioned 2014-03-01T01:53:21Z
dc.date.available 2014-03-01T01:53:21Z
dc.date.issued 2004 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/26977
dc.subject Censored Data en
dc.subject cumulant en
dc.subject Frailty Model en
dc.subject Hazard Function en
dc.subject Nonparametric Maximum Likelihood Estimator en
dc.subject Nuisance Parameter en
dc.subject Proportional Hazard Model en
dc.subject Statistical Inference en
dc.subject Transformation Model en
dc.subject Truncated Data en
dc.subject Inverse Gaussian en
dc.title Frailty Models for Arbitrarily Censored and Truncated Data en
heal.type journalArticle en
heal.identifier.primary 10.1007/s10985-004-4773-y en
heal.identifier.secondary http://dx.doi.org/10.1007/s10985-004-4773-y en
heal.publicationDate 2004 en
heal.abstract In this paper, we propose a frailty model for statistical inference in the case where we are faced with arbitrarily censored and truncated data. Our results extend those of Alioum and Commenges (1996), who developed a method of fitting a proportional hazards model to data of this kind. We discuss the identifiability of the regression coefficients involved in the model en
heal.journalName Lifetime Data Analysis en
dc.identifier.doi 10.1007/s10985-004-4773-y en


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