调解
R包
因果分析
一套
计算机科学
过程(计算)
因果推理
随机试验
数据科学
结构方程建模
因果模型
计量经济学
心理学
管理科学
机器学习
统计
程序设计语言
数学
工程类
考古
法学
历史
政治学
作者
Dustin Tingley,Teppei Yamamoto,K. Hirose,Luke Keele,Kosuke Imai
标识
DOI:10.18637/jss.v059.i05
摘要
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.
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