Gaining more flexibility in Cox proportional hazards regression models with cubic spline functions.
The Cox proportional hazards model is the most popular model for the analysis of survival data. The use of cubic spline functions allows investigation of non-linear effects of continuous covariates and flexible assessment of time-by-covariate interactions. Two main advantages are provided--no particular functional form has to be specified and standard computer software packages like SAS or BMDP can be used. A SAS macro which implements the method is presented.
Heinzl
H
H
Department of Medical Computer Sciences, University of Vienna, Austria. Harald.Heinzl@AKH-Wien.AC.AT
Kaider
A
A
D000964:Antimetabolites, Antineoplastic / Q000627:therapeutic use; D002986:Clinical Trials as Topic; D003627:Data Interpretation, Statistical; D006801:Humans; D007938:Leukemia / Q000188:drug therapy; D008432:Mathematical Computing; D015122:Mercaptopurine / Q000627:therapeutic use; D016016:Proportional Hazards Models; D012984:Software; D012985:Software Design
D000964:Antimetabolites, Antineoplastic; D015122:Mercaptopurine