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

Abstract Details

Activity Number: 624
Type: Contributed
Date/Time: Thursday, August 5, 2010 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract - #307461
Title: Quantile Regression Methods for Doubly Censored Data from Registry Studies
Author(s): Shuang Ji*+ and Limin Peng+ and Yu Cheng and Huichuan Lai
Companies: Emory University and Emory University and University of Pittsburgh and University of Wisconsin
Address: , Atlanta, GA, 30322, 1518 Clifton Rd NE 3rd FL, Atlanta, GA, 30322,
Keywords: quantile regression ; survival analysis ; doubly censored data ; martingale ; varying-effects model

Quantile regression is known for its flexibility of accommodating varying covariate effects and has attracted growing interests in its application to survival analysis. Based on Peng and Huang (2008)'s work on quantile regression method with randomly right censored data, we develop a quantile regression method for a double censoring setting often encountered in registry studies utilizing the embedded martingale structure. The proposed estimation and inference procedures are computationally simple and stable. We establish the uniform consistency and weak convergence of the resulting estimators. We also provide a sensible solution to address the identifiability issues on regression quantiles at both tails, a unique feature with doubly censored data. The finite-sample performance of our approach is assessed by a series of simulation studies. An application to a registry data on cystic fibr

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