Censored regression quantiles

被引:373
作者
Portnoy, S [1 ]
机构
[1] Univ Illinois, Dept Stat, Champaign, IL 61820 USA
基金
美国国家科学基金会;
关键词
accelerated failure time; Bahadur representation; censored data; cox proportional hazard; Kaplan-Meier; regression quantiles;
D O I
10.1198/016214503000000954
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 [统计学]; 070103 [概率论与数理统计]; 0714 [统计学];
摘要
Using quantile regression to analyze survival times offers an valuable complement to traditional Cox proportional hazards modelling. Unfortunately, this approach has been hampered by the lack of a conditional quantile estimator for censored data that is directly analogous to the Kaplan-Meier estimator and applies under standard assumptions for censored regression models. Here a recursively reweighted estimator of the regression quantile process is developed as a direct generalization of the Kaplan-Meier estimator. Specifically, the asymptotic behavior is directly analogous to that of the Kaplan-Meier estimator, and computation is essentially equivalent to current simplex. methods for the quantile process in the uncensored case. Some preliminary examples suggest the strong potential of these methods as a complement to the use of Cox models.
引用
收藏
页码:1001 / 1012
页数:12
相关论文
共 31 条
[1]
Simple resampling methods for censored regression quantiles [J].
Bilias, Y ;
Chen, SN ;
Ying, ZL .
JOURNAL OF ECONOMETRICS, 2000, 99 (02) :373-386
[2]
Generalised bootstrap in non-regular M-estimation problems [J].
Bose, A ;
Chatterjee, S .
STATISTICS & PROBABILITY LETTERS, 2001, 55 (03) :319-328
[3]
An alternative estimator for the censored quantile regression model [J].
Buchinsky, M ;
Hahn, JY .
ECONOMETRICA, 1998, 66 (03) :653-671
[4]
CHEROZHUKOV V, 2001, J AM STAT ASSOC, P872
[5]
EFRON B, 1967, 5TH P BERK S, V4, P831
[6]
Fitzenberger B., 1997, HANDB STAT, V15, P405
[7]
GUTENBRUNNER C, 1993, J NONPARAMETR STAT, V2, P302
[8]
Markov chain marginal bootstrap [J].
He, XM ;
Hu, FF .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2002, 97 (459) :783-795
[10]
Quantile regression under random censoring [J].
Honoré, B ;
Khan, S ;
Powell, JL .
JOURNAL OF ECONOMETRICS, 2002, 109 (01) :67-105