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Bounds on causal effects in randomized trials with noncompliance under monotonicity assumptions about covariates.

机译:在关于协变量的单调性假设下的不合规随机试验中因果效应的界限。

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摘要

In randomized trials with nonrandom noncompliance, the causal effects of a treatment among the entire population cannot be estimated in an unbiased manner. Therefore, several authors have considered the bounds on the causal effects. Here, we propose bounds by applying an idea of VanderWeele (Biometrics 2008; 64:702-706), who showed that the sign of the unmeasured confounding bias can be determined under monotonicity assumptions about covariates in the framework of observational studies. In randomized trials with noncompliance by switching the treatment, we show that the lower or upper bound on the expectation of the potential outcome becomes the expectation from the per-protocol analysis under monotonicity assumptions similar to those of VanderWeele. In particular, the monotonicity assumptions can yield both the lower and the upper bounds on causal effects when the monotonic relationship between the covariates and the treatment actually received depends on the treatment assigned. The results are extended to cases of noncompliance by subjects not receiving any treatment. Although the monotonicity assumptions are not themselves identifiable, they are nonetheless reasonable in some situations.
机译:在具有非随机不依从性的随机试验中,不能以无偏见的方式估算整个人群中治疗的因果关系。因此,几位作者考虑了因果效应的界限。在这里,我们通过应用范德韦勒(VanderWeele)(Biometrics 2008; 64:702-706)的思想提出界线,范德韦勒(VanderWeele)表明,可以在观测研究框架内关于协变量的单调性假设下确定未测混杂混杂的迹象。在通过切换治疗而出现的不依从的随机试验中,我们表明,在类似于VanderWeele的单调性假设下,对潜在结果预期的下限或上限变成了按方案分析的预期。特别是,当协变量与实际接受的治疗之间的单调关系取决于所分配的治疗时,单调性假设既可以产生因果效应的下限,也可以产生上限。结果被扩展到未接受任何治疗的受试者的不依从情况。尽管单调性假设本身无法识别,但在某些情况下仍是合理的。

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