Hernán Miguel A
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA; Harvard-MIT Division of Health Sciences and Technology, Boston, MA.
Ann Epidemiol. 2016 Oct;26(10):674-680. doi: 10.1016/j.annepidem.2016.08.016. Epub 2016 Aug 31.
"Can this number be interpreted as a causal effect?" is a key question for scientists and decision makers. The potential outcomes approach, a quantitative counterfactual theory, describes conditions under which the question can be answered affirmatively. This article reviews one of those conditions, known as consistency, and its implications for real world decisions.
“这个数字能否被解释为一种因果效应?”这是科学家和决策者面临的一个关键问题。潜在结果方法,一种定量反事实理论,描述了在哪些条件下这个问题可以得到肯定的回答。本文回顾了其中一个条件,即一致性,及其对现实世界决策的影响。