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SURVIVAL ANALYSIS

Local Linear Regression in Proportional Hazards Model with Censored Data

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Pages 2761-2776 | Received 21 Jan 2005, Accepted 19 Jan 2007, Published online: 06 Nov 2007
 

Abstract

In this article we study the method of nonparametric regression based on a transformation model, under which an unknown transformation of the survival time is nonlinearly, even more, nonparametrically, related to the covariates with various error distributions, which are parametrically specified with unknown parameters. Local linear approximations and locally weighted least squares are applied to obtain estimators for the effects of covariates with censored observations. We show that the estimators are consistent and asymptotically normal. This transformation model, coupled with local linear approximation techniques, provides many alternatives to the more general proportional hazards models with nonparametric covariates.

Mathematics Subject Classification:

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