mediation: R Package for Causal Mediation Analysis

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.

[1]  J. Pearl.  Interpretation and Identification of Causal Mediation , 2013, Psychological methods.

[2]  W. Wien,et al.  Object-oriented Computation of Sandwich Estimators , 2006 .

[3]  Kosuke Imai,et al.  Comment on Pearl: Practical implications of theoretical results for causal mediation analysis. , 2014, Psychological methods.

[4]  Dustin Tingley,et al.  Causal Mediation Analysis , 2011 .

[5]  Kosuke Imai,et al.  Unpacking the Black-Box: Learning about Causal Mechanisms from Experimental and Observational Studies , 2011 .

[6]  W. Shadish,et al.  Experimental and Quasi-Experimental Designs for Generalized Causal Inference , 2001 .

[7]  L. Keele,et al.  Identification, Inference and Sensitivity Analysis for Causal Mediation Effects , 2010, 1011.1079.

[8]  Bradley Efron,et al.  Bootstrap Condence Intervals , 1996 .

[9]  D. Mackinnon,et al.  Multilevel Modeling of Individual and Group Level Mediated Effects , 2001, Multivariate behavioral research.

[10]  Teppei Yamamoto,et al.  Identification and Estimation of Causal Mediation Effects with Treatment Noncompliance , 2014 .

[11]  L. Keele,et al.  A General Approach to Causal Mediation Analysis , 2010, Psychological methods.

[12]  Klaus Reinhardt,et al.  Advances In Social Science Research Using R , 2016 .

[13]  Kosuke Imai,et al.  Experimental designs for identifying causal mechanisms , 2013 .

[14]  Joshua D. Angrist,et al.  Identification of Causal Effects Using Instrumental Variables , 1993 .

[15]  Kosuke Imai,et al.  Causal Mediation Analysis Using R , 2010 .

[16]  D. A. Kenny,et al.  The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. , 1986, Journal of personality and social psychology.

[17]  Judea Pearl,et al.  Direct and Indirect Effects , 2001, UAI.

[18]  Kosuke Imai,et al.  Experimental Designs for Identifying Causal Mechanisms (with discussions) , 2013 .

[19]  D. Bates,et al.  Linear Mixed-Effects Models using 'Eigen' and S4 , 2015 .

[20]  T. Haavelmo.  The Statistical Implications of a System of Simultaneous Equations , 1943 .

[21]  D. Mackinnon.  Introduction to Statistical Mediation Analysis , 2008 .

[22]  Nicholas A. Valentino,et al.  What Triggers Public Opposition to Immigration? Anxiety, Group Cues, and Immigration Threat , 2008 .

[23]  J. Robins,et al.  Identifiability and Exchangeability for Direct and Indirect Effects , 1992, Epidemiology.

[24]  Kosuke Imai,et al.  mediation : R package for causal mediation analysis Citation , 2014 .

[25]  A. Vinokur,et al.  Impact of the JOBS intervention on unemployed workers varying in risk for depression , 1995, American journal of community psychology.

[26]  Kristopher J Preacher,et al.  Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models , 2008, Behavior research methods.

[27]  B. Efron,et al.  Bootstrap confidence intervals , 1996 .

[28]  Kosuke Imai,et al.  Identification and Sensitivity Analysis for Multiple Causal Mechanisms: Revisiting Evidence from Framing Experiments , 2013, Political Analysis.

[29]  Kristopher J Preacher,et al.  Testing Multilevel Mediation Using Hierarchical Linear Models , 2008 .

[30]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .