"On Sufficient Dimension Reduction for Proportional Censorship Model wi" by Xuerong Meggie Wen
 

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

International Standard Serial Number (ISSN)

0167-9473

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.

Publication Date

01 Jan 2010

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