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Survival Analysis Using a Censored Semiparametric Regression Model

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  • Núñez Antón, Vicente Alfredo
  • Orbe Lizundia, Jesús María
  • Ferreira García, María Eva

Abstract

In this work we study the effect of several covariates X on a censored response variable T with unknown probability distribution. A semiparametric model is proposed to consider situations where the functional form of the effect of one or more covariates is unknown. We provide its estimation procedure and, in addition, a bootstrap technique to make inference on the parameters. An application with a real dataset is presented, as well as some simulation results, to demonstrate the good behavior of the proposed estimation process and to analyze the effect of the censorship. This new model has an important application field in reliability, survival or lifetime data analysis.

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Bibliographic Info

Paper provided by Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística) in its series BILTOKI with number 2000-07.

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Date of creation: Apr 2000
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Handle: RePEc:ehu:biltok:200007

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Postal: Dpto. de Econometría y Estadística, Facultad de CC. Económicas y Empresariales, Universidad del País Vasco, Avda. Lehendakari Aguirre 83, 48015 Bilbao, Spain
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Related research

Keywords: censorship; Kaplan-Meier; lifetime data models; bootstrap; nonparametric estimation;

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  1. Stute, W., 1993. "Consistent Estimation Under Random Censorship When Covariables Are Present," Journal of Multivariate Analysis, Elsevier, vol. 45(1), pages 89-103, April.
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