| 胡纯严,胡良平.基于因果图模型构造和搜索调整集[J].四川精神卫生杂志,2022,35(4):297-301.Hu Chunyan,Hu Liangping,Constructing and searching adjustment sets based on a causal graph model[J].SICHUAN MENTAL HEALTH,2022,35(4):297-301 |
| 基于因果图模型构造和搜索调整集 |
| Constructing and searching adjustment sets based on a causal graph model |
| 投稿时间：2022-07-10 |
| DOI：10.11886/scjsws20220710002 |
| 中文关键词: 因果图模型 因果效应 处理变量 工具变量 调整集 |
| 英文关键词:Causal graph model Causal effect Treatment variable Instrumental variable Adjustment set |
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| 中文摘要: |
| 本文目的是介绍因果图模型的基础知识、因果图过程的内容以及基于SAS/STAT中的CAUSALGRAPH过程构造和搜索调整集的方法。因果图模型是图论与概率论相结合的产物，它可以基于用户设定的变量之间的作用关系找到包含最小调整集在内的所有可能的调整集。因果图过程的内容主要包括三种识别标准、两种操作模式和一种验证检查方法。本文基于SAS中因果图过程对两个实例进行因果效应分析，并对输出结果做出解释。 |
| 英文摘要: |
| The purpose of this paper was to introduce the basic knowledge of the causal graph model， the contents of the CAUSALGRAPH procedure and the method of constructing and searching adjustment sets based on the CAUSALGRAPH procedure in SAS/STAT. The causal graph model was the product of the combination of graph theory and probability theory. It could find all possible adjustment sets including the minimum adjustment set based on the action relationship between the variables set by the user. The contents of the CAUSALGRAPH procedure mainly included three identification criteria， two operating modes and one verification checking method. This paper analyzed the causal effect of two instances based on the CAUSALGRAPH procedure in SAS， and explained the output results. |
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