反事实思维
结果(博弈论)
调解
心理学
结构方程建模
调解人
集合(抽象数据类型)
因果推理
因果模型
计算机科学
统计
计量经济学
社会心理学
数学
医学
政治学
机器学习
内科学
数理经济学
程序设计语言
法学
作者
Matthew J. Valente,Judith J. M. Rijnhart,Heather L. Smyth,Felix B. Muniz,David P. MacKinnon
标识
DOI:10.1080/10705511.2020.1777133
摘要
Mediation analysis is a methodology used to understand how and why an independent variable (X) transmits its effect to an outcome (Y) through a mediator (M). New causal mediation methods based on the potential outcomes framework and counterfactual framework are a seminal advancement for mediation analysis, because they focus on the causal basis of mediation analysis. There are several programs available to estimate causal mediation effects, but these programs differ substantially in data set up, estimation, output, and software platform. To compare these programs, an empirical example is presented, and a single mediator model with treatment-mediator interaction was estimated with a continuous mediator and a continuous outcome in each program. Even though the software packages employ different estimation methods, they do provide similar causal effect estimates for mediation models with a continuous mediator and outcome. A detailed explanation of program similarities, unique features, and recommendations is discussed.
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