Causal mediation analysis
Causal mediation analysis
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DOI：
10.1177/1536867x1101100407
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发表时间：
2011-01-01
期刊：
影响因子：
4.8
通讯作者：
Tingley, Dustin
中科院分区：
文献类型：
--
作者：
Hicks, Raymond;Tingley, Dustin
估计解释变量与被解释变量之间的联系机制，也被称为“中介分析”，是各种社会科学领域的核心，特别是心理学，越来越多地被用于流行病学等领域。最近关于调解分析背后的统计方法的工作指出了早期方法的局限性。我们在统计方法的调解分析的最新发展的基础上，在Stata计算方法。特别是，我们提供了使用几种不同类型的参数模型正确计算因果中介效应的功能，以及计算违反因果解释中介结果所需的关键识别假设的敏感性分析。
Estimating the mechanisms that connect explanatory variables with the explained variable, also known as "mediation analysis," is central to a variety of social-science fields, especially psychology, and increasingly to fields like epidemiology,. Recent work on the statistical methodology behind mediation analysis points to limitations in earlier methods. We implement in Stata computational approaches based on recent developments in the statistical methodology of mediation analysis. In particular, we provide functions for the correct calculation of causal mediation effects using several different types of parametric models, as well as the calculation of sensitivity analyses for violations to the key identifying assumption required for interpreting mediation results causally.