mediation: R Package for Causal Mediation Analysis

被引:0
|
作者
Tingley, Dustin [1 ]
Yamamoto, Teppei [2 ]
Hirose, Kentaro [3 ]
Keele, Luke [4 ]
Imai, Kosuke [3 ]
机构
[1] Harvard Univ, Dept Govt, Cambridge, MA 02138 USA
[2] MIT, Dept Polit Sci, Cambridge, MA 02139 USA
[3] Princeton Univ, Dept Polit, Princeton, NJ 08544 USA
[4] Penn State Univ, Dept Polit Sci, University Pk, PA 16802 USA
来源
JOURNAL OF STATISTICAL SOFTWARE | 2014年 / 59卷 / 05期
关键词
causal mechanisms; mediation analysis; mediation; R; SENSITIVITY-ANALYSIS; IDENTIFICATION; MECHANISMS;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
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.
引用
收藏
页数:38
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