FLEXIBLE COVARIATE EFFECTS IN THE PROPORTIONAL HAZARDS MODEL

被引：26
|
作者：
HASTIE, T
SLEEPER, L
TIBSHIRANI, R
机构：
[1] AT&T BELL LABS,STAT & DATA ANAL RES DEPT,MURRAY HILL,NJ 07974
[2] UNIV TORONTO,DEPT PREVENT MED & BIOSTAT,TORONTO M5S 1A1,ONTARIO,CANADA
[3] UNIV TORONTO,DEPT STAT,TORONTO M5S 1A1,ONTARIO,CANADA
来源：
BREAST CANCER RESEARCH AND TREATMENT | 1992年 / 22卷 / 03期
关键词：
BREAST CANCER; CLINICAL TRIALS; COX REGRESSION MODEL; GENERALIZED ADDITIVE MODEL; NONLINEAR PROGNOSTIC FACTOR MODELING; PROPORTIONAL HAZARDS; REGRESSION SPLINES; SMOOTHING SPLINES;
D O I：
10.1007/BF01840837
中图分类号：
R73 [肿瘤学];
学科分类号：
100214 ;
摘要：
The proportional hazards model is frequently used in analyzing the results of clinical trials, when it is often the case that the outcomes are right-censored. This model allows one to measure treatment effects and simultaneously identify and adjust for prognostic factors that might influence the outcome. In this paper, we outline a class of semiparametric models that allows one to model prognostic factors nonlinearly, and have the data suggest the form of their effect. The methods are illustrated in an analysis of data from a breast cancer clinical trial.
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页码：241 / 250
页数：10
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