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.

中文翻译：

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带有五参数样条模型的惩罚 Cox 回归

摘要

具有三次样条函数的风险模型与现有的回归模型相比具有许多优点。为了分析右删失数据，我们引入了一种使用五个 M 样条基函数的惩罚 Cox 回归方法。所提出的样条模型比现有的参数模型更灵活，因为它产生递增、递减、凸、凹和恒定的危险函数。为了说明所提出模型的优势，我们分析了关于电绝缘的寿命测试数据集和关于肺癌患者的基因表达数据集。我们进行模拟研究以将所提出的方法与现有方法进行比较。