使用结构嵌套失效时间模型估计时变治疗对事件发生时间的因果效应
Estimating the causal effect of a time-varying treatment on time-to-event using structural nested failure time models
摘要：
在本文中，我们回顾了一种方法来估计因果关系的时间变化的治疗时间的一些感兴趣的事件。这种方法被设计用于治疗可能已经反复适应患者特征的情况，这些特征本身也可能是时间依赖性的。在这种情况下，不能简单地通过调节患者特征来估计治疗效果，因为这些特征本身可能是治疗效果的指标。这种所谓的时间依赖性混杂在观察性研究中很常见。我们讨论了一类新的故障时间模型，结构嵌套故障时间模型，它可以用来估计随时间变化的治疗的因果关系，并提出了估计和测试这些模型的参数的方法。
英文摘要：
In this paper we review an approach to estimating the causal effect of a time-varying treatment on time to some event of interest. This approach is designed for the situation where the treatment may have been repeatedly adapted to patient characteristics, which themselves may also be time-dependent. In this situation the effect of the treatment cannot simply be estimated by conditioning on the patient characteristics, as these may themselves be indicators of the treatment effect. This so-called time-dependent confounding is typical in observational studies. We discuss a new class of failure time models, structural nested failure time models, which can be used to estimate the causal effect of a time-varying treatment, and present methods for estimating and testing the parameters of these models.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
