R语言进行COX时变系数模型（含时间依存协变量的Cox回归模型）

我们在临床研究中，经常要研究疾病与生存率的关系，cox回归是用得比较常见的模型之一。Cox 比例风险模型依赖于风险随时间变化的假设（PH假设），意思是协变量对结局的影响随着时间变化是固定的。然而现实中常有不满足于PH假设的情况。如文章：All-cause and cause-specific mortality associated with diabetes in prevalent hemodialysis patients中 道了一个人的糖尿病状态可能会随着时间而变化，尿毒症患者肾功能随着时间变化加重，因此Cox 比例风险模型用在此处不合适，我们可以选用COX回归模型的扩展，一般有两种内在和外部，见下图

survival包自带的cox.zph函数可以用于PH假设的检查

这样我们就多了一个新指标tgroup，如下图

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