title: Gaining more flexibility in Cox proportional hazards regression models with cubic spline functions.
abstract: 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.
authors.affiliation: Department of Medical Computer Sciences, University of Vienna, Austria. Harald.Heinzl@AKH-Wien.AC.AT
authors.forename: H
authors.initials: H
authors.lastname: Heinzl
authors.forename: A
authors.initials: A
authors.lastname: Kaider
mesh_terms: 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
chemical_list: D000964:Antimetabolites, Antineoplastic; D015122:Mercaptopurine