当前位置: X-MOL 学术Annu. Rev. Stat. Appl. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Causality and the Cox Regression Model
Annual Review of Statistics and Its Application ( IF 7.4 ) Pub Date : 2022-03-07 , DOI: 10.1146/annurev-statistics-040320-114441
Torben Martinussen 1
Affiliation  

This article surveys results concerning the interpretation of the Cox hazard ratio in connection to causality in a randomized study with a time-to-event response. The Cox model is assumed to be correctly specified, and we investigate whether the typical end product of such an analysis, the estimated hazard ratio, has a causal interpretation as a hazard ratio. It has been pointed out that this is not possible due to selection. We provide more insight into the interpretation of hazard ratios and differences, investigating what can be learned about a treatment effect from the hazard ratio approaching unity after a certain period of time. The conclusion is that the Cox hazard ratio is not causally interpretable as a hazard ratio unless there is no treatment effect or an untestable and unrealistic assumption holds. We give a hazard ratio that has a causal interpretation and study its relationship to the Cox hazard ratio.

中文翻译:


因果关系和 Cox 回归模型

本文调查了一项随机研究中与因果关系相关的 Cox 风险比解释的结果,该研究具有事件时间响应。假设 Cox 模型是正确指定的,我们调查这种分析的典型最终产品,即估计的风险比,是否具有作为风险比的因果解释。已经指出,由于选择,这是不可能的。我们对风险比和差异的解释提供了更深入的了解,调查了在一段时间后从接近统一的风险比可以了解的治疗效果。结论是,除非没有治疗效果或存在不可检验和不切实际的假设,否则 Cox 风险比不能因果解释为风险比。

更新日期:2022-03-07
down
wechat
bug