Role of covariates in the analysis of causal mediation effects
10.11886/scjsws20220911001
- VernacularTitle:协变量在因果中介效应分析中的作用
- 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;
Treatment variable;
Mediation variable;
Outcome variable;
Confounding variable
- From:
Sichuan Mental Health
2022;35(5):402-406
- CountryChina
- Language:Chinese
-
Abstract:
The purpose of this paper was to introduce the theoretical basis of the causal mediation effect analysis and the specific method to realize an example by the causal mediation effect analysis with SAS. The theoretical basis of the causal mediation effect analysis included the following two aspects， the basic concept and defining the counterfactual framework of the causal mediation effect. The example was about whether the encouraging environment provided by parents would affect the cognitive development of children. The traditional multiple linear regression analysis， the causal mediation effect analysis without considering covariates and with considering covariates were used， respectively. By comparing the results obtained by the three analysis methods， the following conclusions were drawn： ① when there were the mediation variables in the data， it was not suitable to use traditional multiple linear regression analysis to replace the causal mediation effect analysis； ② when there were covariates in the data， it was not suitable to conduct causal mediation analysis under the condition of ignoring covariates.
