摘要
本文目的是介绍因果图过程的5个局限性和基于因果图模型应用调整集估计数据的因果效应。5个局限性包括:①因果图过程不能处理有向循环的因果图模型;②因果图过程不能评估动态处理方案;③因果效应识别是一个总体概念;④因果效应识别是一个非参数概念;⑤因果图过程不能识别某些因果图模型中的因果效应。实例是针对一个模拟的数据集,分别采用常规的多重Logistic回归模型分析与因果图模型分析,比较二者的分析结果,得出如下结论:①因果图理论在混淆情况下识别因果效应是有用的;②通过实施因果效应的分层估计,可以基于因果图过程的识别结果,实现因果效应的良好统计估计。
The purpose of this paper was to introduce the five limitations of the PROC CAUSALGRAPH procedure and estimate the causal effect of the data by using the adjustment set based on the causal graph model.The five limitations were as follows:①the PROC CAUSALGRAPH procedure could not deal with the causal graph model of directed circles;②the PROC CAUSALGRAPH procedure could not evaluate dynamic processing scheme;③causal effect identification was a population concept;④causal effect identification was a nonparametric concept;⑤the PROC CAUSALGRAPH procedure could not identify the causal effect in some causal graph models.The example was for a simulated data set,using the conventional multiple Logistic regression model analysis and the causal graph model analysis,respectively.By comparing the analysis results of the two,the following conclusions were drawn:①causal graph theory was useful in identifying causal effects in confounding situations;②by implementing hierarchical estimation of causal effects,a good statistical estimation of causal effects could be achieved based on the identification results of the PROC CAUSALGRAPH procedure.
作者
胡纯严
胡良平
Hu Chunyan;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)
出处
《四川精神卫生》
2022年第4期313-318,共6页
Sichuan Mental Health
关键词
因果图模型
因果效应
分层估计
处理效应
Causal graph model
Causal effect
Hierarchical estimation
Treatment effect
