ABSTRACT 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.

中文翻译：

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R、Mplus、SAS、SPSS 和 Stata 中的因果调解程序

摘要 中介分析是一种用于了解自变量 (X) 如何以及为何通过中介 (M) 将其影响传递给结果 (Y) 的方法。基于潜在结果框架和反事实框架的新因果中介方法是中介分析的开创性进步，因为它们关注中介分析的因果基础。有几种程序可用于估计因果中介效应，但这些程序在数据设置、估计、输出和软件平台方面存在很大差异。为了比较这些程序，我们提供了一个经验示例，并在每个程序中使用连续中介和连续结果来估计具有治疗-中介相互作用的单个中介模型。即使软件包采用不同的估计方法，它们确实为具有连续中介和结果的中介模型提供了类似的因果效应估计。讨论了程序相似性、独特功能和建议的详细说明。