Frailty Models for Arbitrarily Censored and Truncated Data

Huber-Carol, C; Vonta, I

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