关于存在不依从情况的随机试验中因果效应估计的可识别性说明。
A note about the identifiability of causal effect estimates in randomized trials with non-compliance.
作者信息
Chan Kwun Chuen Gary
机构信息
Departments of Biostatistics and Health Services, University of Washington, Seattle WA 98195.
出版信息
Stat Methodol. 2014 Jan 1;16. doi: 10.1016/j.stamet.2013.07.003.
Abstract
We show that assumptions that are sufficient for estimating an average treatment effect in randomized trials with non-compliance restrict the subgroup means for always takers, compliers, defiers and never takers to a two dimensional linear subspace of a four dimensional space. Implications and specials cases are examplified.
摘要
我们表明，在存在不依从性的随机试验中，对于估计平均治疗效果而言足够的假设，将始终接受治疗者、依从者、违抗者和从不接受治疗者的亚组均值限制在四维空间的一个二维线性子空间中。文中举例说明了其影响和特殊情况。
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Biometrics. 2009 Jun;65(2):640-9. doi: 10.1111/j.1541-0420.2008.01066.x. Epub 2008 May 28.
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Instruments for causal inference: an epidemiologist's dream?因果推断的工具：流行病学家的梦想？
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