Survival studies often generate not only a survival time for each patient but also a sequence of health measurements at annual or semi-annual check-ups while the patient remains alive. Such a sequence of random length accompanied by a survival time is called a survival process. Robust health is ordinarily associated with longer survival, so the two parts of a survival process cannot be assumed independent. This paper is concerned with a general technique—reverse alignment—for constructing statistical models for survival processes, here termed revival models. A revival model is a regression model in the sense that it incorporates covariate and treatment effects into both the distribution of survival times and the joint distribution of health outcomes. The revival model also determines a conditional survival distribution given the observed history, which describes how the subsequent survival distribution is determined by the observed progression of health outcomes.

中文翻译：

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对“生存模型和健康序列”讨论者的回应。

生存研究通常不仅会为每个患者生成生存时间，而且还会在患者保持生命的同时，每年或半年进行一次健康检查。这样的随机长度序列伴随着生存时间被称为生存过程。健壮的健康通常与更长的生存期相关，因此无法假定生存过程的两个部分是独立的。本文涉及一种用于构建生存过程统计模型的通用技术（反向对齐），此处称为复兴模型。复兴模型是一种回归模型，从某种意义上说，它是将协变量和治疗效果纳入生存时间分布和健康结果的联合分布中。复兴模型还根据观察到的病史确定条件性生存分布，这描述了如何通过观察到的健康结果进展确定后续的生存分布。