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Commentary: Counterfactual causation and streetlamps: what is to be done?

作者信息

Robins James M, Weissman Michael B

机构信息

Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL, USA.

出版信息

Int J Epidemiol. 2016 Dec 1;45(6):1830-1835. doi: 10.1093/ije/dyw231.

DOI:10.1093/ije/dyw231
PMID:28130321
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5841619/
Abstract
摘要

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本文引用的文献

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Commentary: The formal approach to quantitative causal inference in epidemiology: misguided or misrepresented?评论：流行病学中定量因果推断的形式化方法：是被误导了还是被误解了？
Int J Epidemiol. 2016 Dec 1;45(6):1817-1829. doi: 10.1093/ije/dyw227.
2
Commentary: On Causes, Causal Inference, and Potential Outcomes.评论：关于原因、因果推断和潜在结果
Int J Epidemiol. 2016 Dec 1;45(6):1809-1816. doi: 10.1093/ije/dyw230.
3
The tale wagged by the DAG: broadening the scope of causal inference and explanation for epidemiology.二酰甘油讲述的故事：拓宽流行病学因果推断和解释的范围
Int J Epidemiol. 2016 Dec 1;45(6):1787-1808. doi: 10.1093/ije/dyw114.
4
Does water kill? A call for less casual causal inferences.水会致命吗？呼吁减少随意的因果推断。
Ann Epidemiol. 2016 Oct;26(10):674-680. doi: 10.1016/j.annepidem.2016.08.016. Epub 2016 Aug 31.
5
Causality and causal inference in epidemiology: the need for a pluralistic approach.流行病学中的因果关系与因果推断：多元方法的必要性。
Int J Epidemiol. 2016 Dec 1;45(6):1776-1786. doi: 10.1093/ije/dyv341.
6
Is the "well-defined intervention assumption" politically conservative?“明确干预假设”在政治上是保守的吗？
Soc Sci Med. 2016 Oct;166:254-257. doi: 10.1016/j.socscimed.2015.10.054. Epub 2015 Oct 28.
7
Interference and Sensitivity Analysis.干扰与敏感性分析。
Stat Sci. 2014 Nov;29(4):687-706. doi: 10.1214/14-STS479.
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Toward Causal Inference With Interference.迈向具有干扰性的因果推断
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