Constructing and searching adjustment sets based on a causal graph model
10.11886/scjsws20220710002
- VernacularTitle:基于因果图模型构造和搜索调整集
- Author:
Chunyan HU
1
;
Liangping HU
1
Author Information
1. Graduate School， Academy of Military Sciences PLA China， Beijing 100850， China
- Publication Type:Journal Article
- Keywords:
Causal graph model;
Causal effect;
Treatment variable;
Instrumental variable;
Adjustment set
- From:
Sichuan Mental Health
2022;35(4):297-301
- CountryChina
- Language:Chinese
-
Abstract:
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.
