Title

On Sufficient Dimension Reduction for Proportional Censorship Model with Covariates

Editor(s)

Kontoghiorghes, E. J. and Lee, J. C.

Abstract

The requirement of constant censoring parameter β in Koziol-Green (KG) model is too restrictive. When covariates are present, the conditional KG model (Veraverbekea and Cadarso-Suárez, 2000) which allows β 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 β is a function of the covariates. Our method also allows us to conduct a model-free selection of the related covariates. A simulation study and a real data analysis are also included to illustrate our approach.

Department(s)

Mathematics and Statistics

Keywords and Phrases

Conditional Koziol-Green model; Multiple covariates; Proportional hazards model; sufficient dimension reduction

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2010 Research Division of the Federal Reserve Bank of St. Louis, All rights reserved.


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