@article{7088198,
  abstract     = {{Mediation analysis is routinely adopted by researchers from a wide range of applied disciplines as a statistical tool to disentangle the causal pathways by which an exposure or treatment affects an outcome. The counterfactual framework provides a language for clearly defining path-specific effects of interest and has fostered a principled extension of mediation analysis beyond the context of linear models. This paper describes medflex, an R package that implements some recent developments in mediation analysis embedded within the counterfactual framework. The medflex package offers a set of ready-made functions for fitting natural effect models, a novel class of causal models which directly parameterize the path-specific effects of interest, thereby adding flexibility to existing software packages for mediation analysis, in particular with respect to hypothesis testing and parsimony. In this paper, we give a comprehensive overview of the functionalities of the medflex package.}},
  author       = {{Steen, Johan and Loeys, Tom and Moerkerke, Beatrijs and Vansteelandt, Stijn}},
  issn         = {{1548-7660}},
  journal      = {{JOURNAL OF STATISTICAL SOFTWARE}},
  keywords     = {{mediation analysis,R,causal inference,direct effect,indirect effect,medflex,natural effect models,SENSITIVITY-ANALYSIS,CAUSAL MECHANISMS,INFERENCE,IDENTIFICATION,EXPOSURE,DECOMPOSITION,CONFOUNDER,IMPUTATION,VARIABLES,FORMULA}},
  language     = {{eng}},
  number       = {{11}},
  pages        = {{46}},
  title        = {{medflex : an R package for flexible mediation analysis using natural effect models}},
  url          = {{http://doi.org/10.18637/jss.v076.i11}},
  volume       = {{76}},
  year         = {{2017}},
}

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