Instrumental variable analyses. Exploiting natural randomness to understand causal mechanisms.
Instrumental variable analyses. Exploiting natural randomness to understand causal mechanisms.
复制标题
DOI：
10.1513/annalsats.201303-054fr
复制
发表时间：
2013-06-01
影响因子：
8.3
通讯作者：
Kennedy, Edward H
中科院分区：
文献类型：
--
作者：
Iwashyna, Theodore J;Kennedy, Edward H
工具变量分析是社会科学中常用的一种技术，用于提供治疗导致结果的证据，而不是治疗仅与结果差异相关的证据。为了从观察数据中提取如此有力的证据，工具变量分析利用了某种程度的随机性影响患者选择治疗方式的情况。工具变量是世界的一个特征，它导致某些人更有可能获得我们想要研究的特定治疗，但不会改变这些患者的结果。本次研讨会以非数学语言解释了工具变量分析背后的逻辑，包括几个例子。它还提供了工具变量分析的读者在评估证据质量时应提出的三个关键问题。 (1) 工具变量是否会导致所测试的治疗产生有意义的差异？ （2）除了通过正在测试的具体处理之外，工具变量是否还有其他方式影响结果？ (3) 是否有什么因素导致患者既接受工具变量又接受结果？
Instrumental variable analysis is a technique commonly used in the social sciences to provide evidence that a treatment causes an outcome, as contrasted with evidence that a treatment is merely associated with differences in an outcome. To extract such strong evidence from observational data, instrumental variable analysis exploits situations where some degree of randomness affects how patients are selected for a treatment. An instrumental variable is a characteristic of the world that leads some people to be more likely to get the specific treatment we want to study but does not otherwise change those patients' outcomes. This seminar explains, in nonmathematical language, the logic behind instrumental variable analyses, including several examples. It also provides three key questions that readers of instrumental variable analyses should ask to evaluate the quality of the evidence. (1) Does the instrumental variable lead to meaningful differences in the treatment being tested? (2) Other than through the specific treatment being tested, is there any other way the instrumental variable could influence the outcome? (3) Does anything cause patients to both receive the instrumental variable and receive the outcome?