mediation: R Package for Causal Mediation Analysis

Dustin Tingley, Teppei Yamamoto, Kentaro Hirose, Luke Keele and Kosuke Imai

Journal of Statistical Software, 2014, vol. 059, issue i05

Abstract: 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.

Date: 2014-09-02
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Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:059:i05

DOI: 10.18637/jss.v059.i05

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