Semiparametric transformation Models for arbitrarily Censored and truncated data

Autor:	Filia Vonta, Catherine Huber-Carol
Přispěvatelé:	Graffigne, Christine, Mathématiques Appliquées Paris 5 (MAP5 - UMR 8145), Université Paris Descartes - Paris 5 (UPD5)-Institut National des Sciences Mathématiques et de leurs Interactions (INSMI)-Centre National de la Recherche Scientifique (CNRS), Mathématiques Appliquées à Paris 5 ( MAP5 - UMR 8145 ), Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National des Sciences Mathématiques et de leurs Interactions-Centre National de la Recherche Scientifique ( CNRS )
Jazyk:	angličtina
Rok vydání:	2004
Předmět:	Set (abstract data type) Computer science Proportional hazards model Generalization Nonparametric statistics Applied mathematics Regression analysis Transformation models Data mining computer.software_genre computer
Zdroj:	Survival Analysis and Quality of Liife Survival Analysis and Quality of Liife, 2004, pp.167-176 Statistics for Industry and Technology ISBN: 9781461264910
Popis:	A regression analysis for arbitrarily censored and truncated data was proposed by (1996), using Cox’s proportional hazards model, and based on (1976) for nonparametric estimation of a distribution function. We propose here a generalization of their method to the case where there is an unobserved heterogeneity in the data taken into account by a frailty model. Our methodology is applied to a set of real data on transfusion-related AIDS that has been used among others by (1989).
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1d32379f68d263f07b4ba33de765812a https://hal.archives-ouvertes.fr/hal-00262402 Zobrazit plný text záznamu