胡纯严,胡良平.基于工具变量识别因果效应以及用数据区分不同模型[J].四川精神卫生杂志,2022,35(4):307-312.Hu Chunyan,Hu Liangping,Identifying causal effects based on instrumental variables and distinguishing different models with data[J].SICHUAN MENTAL HEALTH,2022,35(4):307-312

基于工具变量识别因果效应以及用数据区分不同模型

Identifying causal effects based on instrumental variables and distinguishing different models with data

投稿时间：2022-07-10

DOI：10.11886/scjsws20220710004

中文关键词: 因果图模型因果效应关联和偏差识别和调整工具变量

英文关键词:Causal graph model Causal effect Association and bias Identification and adjustment Instrumental variables

基金项目:

作者	单位	邮编
胡纯严	军事科学院研究生院，北京 100850	100850
胡良平^*	军事科学院研究生院，北京 100850 世界中医药学会联合会临床科研统计学专业委员会，北京 100029	100029

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中文摘要:

本文目的是介绍基于工具变量识别因果效应、用数据区分不同模型以及使用SAS软件实现计算的方法。首先，介绍因果图理论的4个主要内容，包括关联的来源、因果图模型的统计性质、识别和调整以及工具变量；其次，针对两个实例并借助SAS/STAT中的CAUSALGRAPH过程，完成以下两项任务：①用工具变量识别因果效应；②用数据区分不同模型。

英文摘要:

The purpose of this paper was to introduce the methods of identifying causal effects based on instrumental variables， distinguishing different models with data， and using SAS software to realize calculation. Firstly， the four main contents of causal graph theory were introduced， including sources of association， statistical properties of causal models， identification and adjustment， and instrumental variables. Secondly， for two examples and with the help of the CAUSALGRAPH procedure in SAS/STAT， the following two tasks were completed： the first task was to identify causal effects using instrumental variables； the second task was to use data to distinguish different models.

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