Predicting survival probabilities with semiparametric transformation models

被引:104
作者
Cheng, SC
Wei, LJ
Ying, Z
机构
[1] HARVARD UNIV,DEPT BIOSTAT,BOSTON,MA 02115
[2] RUTGERS STATE UNIV,DEPT STAT,PISCATAWAY,NJ 08855
关键词
gaussian process; martingale; proportional hazards model; proportional odds model; weak convergence;
D O I
10.2307/2291467
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Prediction of survival probabilities for future patients is one of the-main goals of fitting survival data with regression models. In this article we consider a large class of semiparametric transformation models, which includes the well-known proportional hazards and proportional odds models, for the analysis of failure time data. Specifically, we propose pointwise and simultaneous confidence interval procedures for the survival probability of future patients with specific covariates. These procedures can be easily implemented through;simulation and are illustrated with the data from two well-known clinical studies.
引用
收藏
页码:227 / 235
页数:9
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