Penalized Cox regression with a five-parameter spline model

Abstract

Hazard models with cubic spline functions have a number of advantages to the existing regression models. For analysis of right-censored data, we introduce a penalized Cox regression method using five M-spline basis functions. The proposed spline model is more flexible than the existing parametric models as it produces the increasing, decreasing, convex, concave, and constant hazard functions. To illustrate the advantage of the proposed model, we analyze a life test dataset on electrical insulations and a gene expression dataset on lung cancer patients. We conduct simulation studies to compare the proposed method with the existing methods.