On the Estimation Accuracy of Causal Effects using Supplementary Variables
On the Estimation Accuracy of Causal Effects using Supplementary Variables
复制标题
关于使用补充变量的因果效应估计准确性
DOI：
10.1111/sjos.12188
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发表时间：
2016
影响因子：
1
通讯作者：
Manabu Kuroki,Takahiro Hayashi
中科院分区：
文献类型：
--
作者：
Manabu Kuroki,Takahiro Hayashi
本文主要讨论一组处理通过线性模型和离散模型中的一组补充变量与响应相关联的情况。在这种情况下，我们证明了从补充变量集可以更准确地估计因果关系。此外，我们还证明了补充变量集可以包括选择变量和代理变量。此外，我们提出了基于因果效应估计精度的补充变量选择标准。根据我们的结果，我们可以从图的结构中判断出某些情况，在这种情况下，通过补充变量可以更准确地估计因果关系，并且可以从观测数据中可靠地评估因果关系。
This paper focuses on a situation in which a set of treatments is associated with a response through a set of supplementary variables in linear models as well as discrete models. Under the situation, we demonstrate that the causal effect can be estimated more accurately from the set of supplementary variables. In addition, we show that the set of supplementary variables can include selection variables and proxy variables as well. Furthermore, we propose selection criteria for supplementary variables based on the estimation accuracy of causal effects. From graph structures based on our results, we can judge certain situations under which the causal effect can be estimated more accurately by supplementary variables and reliably evaluate the causal effects from observed data.