Analysis of transformation models with censored data

被引:122
作者
Cheng, SC
Wei, LJ
Ying, Z
机构
[1] HARVARD UNIV,DEPT BIOSTAT,BOSTON,MA 02115
[2] RUTGERS STATE UNIV,DEPT STAT,NEW BRUNSWICK,NJ 08903
关键词
generalised estimating equation; martingale; proportional hazards model; proportional odds model; U-statistic;
D O I
10.2307/2337348
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
In this paper we consider a class of semi-parametric transformation models, under which an unknown transformation of the survival time is linearly related to the covariates with various completely specified error distributions. This class of regression models includes the proportional hazards and proportional odds models. Inference procedures derived from a class of generalised estimating equations are proposed to examine the covariate effects with censored observations. Numerical studies are conducted to investigate the properties of our proposals for practical sample sizes. These transformation models, coupled with the new simple inference procedures, provide many useful alternatives to the Cox regression model in survival analysis.
引用
收藏
页码:835 / 845
页数:11
相关论文
共 19 条
[1]   COX REGRESSION-MODEL FOR COUNTING-PROCESSES - A LARGE SAMPLE STUDY [J].
ANDERSEN, PK ;
GILL, RD .
ANNALS OF STATISTICS, 1982, 10 (04) :1100-1120
[2]  
Bennett S, 1983, Stat Med, V2, P273, DOI 10.1002/sim.4780020223
[3]  
BICKEL PJ, 1986, PAPERS SEMIPARAMETRI, P63
[4]   AN ANALYSIS OF TRANSFORMATIONS [J].
BOX, GEP ;
COX, DR .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 1964, 26 (02) :211-252
[5]  
CLAYTON DG, 1986, P INT STATIST I AMST
[6]   PARTIAL LIKELIHOOD [J].
COX, DR .
BIOMETRIKA, 1975, 62 (02) :269-276
[7]  
COX DR, 1972, J R STAT SOC B, V34, P187
[8]   RANK REGRESSION [J].
CUZICK, J .
ANNALS OF STATISTICS, 1988, 16 (04) :1369-1389
[9]  
DABROWSKA DM, 1988, SCAND J STAT, V15, P1
[10]   ESTIMATION AND TESTING IN A 2-SAMPLE GENERALIZED ODDS-RATE MODEL [J].
DABROWSKA, DM ;
DOKSUM, KA .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1988, 83 (403) :744-749