This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 441
Type: Invited
Date/Time: Wednesday, August 4, 2010 : 8:30 AM to 10:20 AM
Sponsor: WNAR
Abstract - #306082
Title: Variable Selection in Censored Quantile Regression
Author(s): Huixia Wang*+ and Jianhui Zhou
Companies: North Carolina State University and University of Virginia
Address: , Raleigh, NC, 27695, USA
Keywords: Censored ; Dimension reduction ; Quantile regression ; Survival analysis ; Variable Selection
Abstract:

Quantile regression provides a valuable supplement to Cox proportional hazards model for analyzing survival data where censoring is common. In contrast to conventional statistical methods, quantile regression models can help discover heterogeneous effects of drug treatments on survival times of both high and low risk patients. Existing methods for censored quantile regression often require stringent assumptions such as linearity of all quantile functions, which restrict model flexibility and complicate computation. In this talk, I will first present an index-based estimation method for censored quantile regression to accommodate high dimensional covariates. Then I will discuss penalization methods for variable selection, including selection of groups of correlated covariates, in censored quantile regression.


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