Key technology and multi-directional decomposition method of the causal mediation effect analysis
10.11886/scjsws20220911002
- VernacularTitle:因果中介效应分析的关键技术和多向分解方法
- 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 mediation effect;
Effect identification;
Maximum likelihood estimation;
Bootstrap method;
Multi-way decomposition
- From:
Sichuan Mental Health
2022;35(5):407-411
- CountryChina
- Language:Chinese
-
Abstract:
The purpose of this paper was to introduce five key techniques and the multi-directional decomposition methods of effect components in the analysis of causal mediation effects. The contents of the five key technologies were as follows： ① identification of causal mediation effect； ② regression method of causal mediation effect analysis； ③ maximum likelihood estimation； ④ estimation of total effect and various component effects； ⑤ estimation by bootstrap method. The multi-directional decomposition methods included 3 bidirectional decompositions， 2 three-directional decompositions and 1 four-directional decomposition. Through an example， a causal mediation effect analysis model including covariates and interaction terms was constructed with the help of SAS， bidirectional decomposition， three-directional decomposition and four-directional decomposition were carried out for the total effect in the causal mediation effect analysis， and the output results were explained.
