This paper discusses methods for clustering a continuous covariate in a survival analysis model. The advantages of using a categorical covariate defined from discretizing a continuous covariate (via clustering) is (i) enhanced interpretability of the covariate's impact on survival and (ii) relaxing model assumptions that are usually required for survival models, such as the proportional hazards model. Simulations and an example are provided to illustrate the methods.

中文翻译：

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比例风险模型的最佳划分

本文讨论了在生存分析模型中对连续协变量进行聚类的方法。使用通过离散连续协变量（通过聚类）离散化定义的分类协变量的优点是：（i）增强了协变量对生存的影响的可解释性；（ii）放宽了生存模型通常需要的模型假设，例如比例风险模型。提供了仿真和示例来说明这些方法。