ASSESSING TIME-BY-COVARIATE INTERACTIONS IN PROPORTIONAL HAZARDS REGRESSION-MODELS USING CUBIC SPLINE FUNCTIONS

被引：175
|
作者：
HESS, KR
机构：
[1] Department of Patient Studies, University of Texas, M.D. Anderson Cancer Center, Houston, Texas, 77030-4095, Box 214
来源：
STATISTICS IN MEDICINE | 1994年 / 13卷 / 10期
关键词：
D O I：
10.1002/sim.4780131007
中图分类号：
Q [生物科学];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
Proportional hazards (or Cox) regression is a popular method for modelling the effects of prognostic factors on survival. Use of cubic spline functions to model time-by-covariate interactions in Cox regression allows investigation of the shape of a possible covariate-time dependence without having to specify a specific functional form. Cubic spline functions allow one to graph such time-by-covariate interactions, to test formally for the proportional hazards assumption, and also to test for non-linearity of the time-by-covariate interaction. The functions can be fitted with existing software using relatively few parameters; the regression coefficients are estimated using standard maximum likelihood methods.
引用
收藏
页码：1045 / 1062
页数：18
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