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Activity Number: 605
Type: Contributed
Date/Time: Thursday, August 6, 2009 : 10:30 AM to 12:20 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #303512
Title: Sufficient Dimension Reduction for Proportional Censorship Model with Covariates
Author(s): Meggie Wen*+
Companies: Missouri University of Science and Technology
Address: 202 Rolla Bldg., Rolla, MO, 65409,
Keywords: Sufficient Dimension Reduction ; Proportional Hazards Model ; Conditional Koziol-Green Model ; Multiple Covariates
Abstract:

The requirement of constant censoring parameter $\beta$ in Koziol-Green (KG) model is too restrictive. When covariates are present, the conditional KG model (Veraverbeke and Cadarso-Suarez, 2000) which allows $\beta$ to be dependent on the covariates is more realistic. In this paper, using sufficient dimension reduction methods, we provide a model-free diagnostic tool to test if $\beta$ is a function of the covariates. Our method also allows us to conduct a model-free selection of the related covariates.

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