mediation: R Package for Causal Mediation Analysis
mediation: R Package for Causal Mediation Analysis
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DOI：
10.18637/jss.v059.i05
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发表时间：
2014-09
影响因子：
5.8
通讯作者：
D. Tingley;Teppei Yamamoto;Kentaro Hirose;L. Keele;K. Imai
中科院分区：
文献类型：
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作者：
D. Tingley;Teppei Yamamoto;Kentaro Hirose;L. Keele;K. Imai
在本文中，我们描述了用于在应用实证研究中进行因果中介分析的R包装中介。在许多科学学科中，研究人员的目标不仅在于估计治疗的因果影响，而且还了解治疗因果影响结果的过程。因果中介分析经常用于评估潜在的因果机制。调解软件包实现了进行此类分析的全面统计工具。该软件包被组织为两种不同的方法。使用基于模型的方法，研究人员可以根据标准研究设计估算因果中介效应并进行灵敏度分析。此外，基于设计的方法提供了几种适用于不同实验设计的分析工具。这种方法需要比基于模型的方法更弱的假设。我们还实施了一种统计方法来处理多个（因果关系）调解人，这些方法通常在实践中遇到。最后，该软件包还提供了一种在治疗不遵守治疗的情况下评估因果中介的方法，这是随机试验中的常见问题。
In this paper, we describe the R package mediation for conducting causal mediation analysis in applied empirical research. In many scientific disciplines, the goal of researchers is not only estimating causal effects of a treatment but also understanding the process in which the treatment causally affects the outcome. Causal mediation analysis is frequently used to assess potential causal mechanisms. The mediation package implements a comprehensive suite of statistical tools for conducting such an analysis. The package is organized into two distinct approaches. Using the model-based approach, researchers can estimate causal mediation effects and conduct sensitivity analysis under the standard research design. Furthermore, the design-based approach provides several analysis tools that are applicable under different experimental designs. This approach requires weaker assumptions than the model-based approach. We also implement a statistical method for dealing with multiple (causally dependent) mediators, which are often encountered in practice. Finally, the package also offers a methodology for assessing causal mediation in the presence of treatment noncompliance, a common problem in randomized trials.