Hu Chunyan,Hu Liangping,Constructing and searching adjustment sets based on a causal graph model[J].SICHUAN MENTAL HEALTH,2022,35(4):297-301
Constructing and searching adjustment sets based on a causal graph model
DOI:10.11886/scjsws20220710002
English keywords:Causal graph model  Causal effect  Treatment variable  Instrumental variable  Adjustment set
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Author NameAffiliationPostcode
Hu Chunyan Graduate School Academy of Military Sciences PLA China Beijing 100850 China 100850
Hu Liangping* Graduate School Academy of Military Sciences PLA China Beijing 100850 China
Specialty Committee of Clinical Scientific Research Statistics of World Federation of Chinese Medicine Societies Beijing 100029 China 
100029
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English 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.
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