| 胡纯严,胡良平.因果中介效应分析的关键技术和多向分解方法[J].四川精神卫生杂志,2022,35(5):407-411.Hu Chunyan,Hu Liangping,Key technology and multi-directional decomposition method of the causal mediation effect analysis[J].SICHUAN MENTAL HEALTH,2022,35(5):407-411 |
| 因果中介效应分析的关键技术和多向分解方法 |
| Key technology and multi-directional decomposition method of the causal mediation effect analysis |
| 投稿时间：2022-09-11 |
| DOI：10.11886/scjsws20220911002 |
| 中文关键词: 因果中介效应 效应识别 最大似然估计 自助法 多向分解 |
| 英文关键词:Causal mediation effect Effect identification Maximum likelihood estimation Bootstrap method Multi-way decomposition |
| 基金项目: |
|
| 摘要点击次数: |
| 全文下载次数: |
| 中文摘要: |
| 本文目的是介绍因果中介效应分析的5项关键技术和效应成分多向分解方法。5项关键技术的内容如下：①因果中介效应的识别；②因果中介效应分析的回归方法；③最大似然估计；④总效应与各种成分效应的估计；⑤自助法估计。多向分解方法包括3个双向分解、2个三向分解和1个四向分解。本文通过一个实例，借助SAS构建包含协变量和交互作用项的因果中介效应模型，对因果中介效应分析中的总效应进行双向分解、三向分解和四向分解，并对输出结果进行解释。 |
| 英文摘要: |
| 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. |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| 关闭 |