Please cite the following works when using the 'medoutcon' software package, including both the software tool and the article describing the statistical methodology.

Hejazi NS, Díaz I, Rudolph KE (2026). medoutcon: Efficient causal mediation analysis for the natural and interventional effects. doi:10.5281/zenodo.5809519. R package version 0.2.4, https://github.com/nhejazi/medoutcon.

Hejazi NS, Díaz I, Rudolph KE (2022). “medoutcon: Nonparametric efficient causal mediation analysis with machine learning in R.” Journal of Open Source Software. doi:10.21105/joss.03979. https://doi.org/10.21105/joss.03979.

Díaz I, Hejazi NS, Rudolph KE, van der Laan MJ (2020). “Non-parametric efficient causal mediation with intermediate confounders.” Biometrika. doi:10.1093/biomet/asaa085. https://arxiv.org/abs/1912.09936.

Corresponding BibTeX entries:

  @Manual{,
    title = {{medoutcon}: Efficient causal mediation analysis for the
      natural and interventional effects},
    author = {Nima S Hejazi and Iván Díaz and Kara E Rudolph},
    year = {2026},
    note = {R package version 0.2.4},
    doi = {10.5281/zenodo.5809519},
    url = {https://github.com/nhejazi/medoutcon},
  }

  @Article{,
    journal = {Journal of Open Source Software},
    title = {{medoutcon}: Nonparametric efficient causal mediation
      analysis with machine learning in {R}},
    author = {Nima S Hejazi and Iván Díaz and Kara E Rudolph},
    year = {2022},
    doi = {10.21105/joss.03979},
    url = {https://doi.org/10.21105/joss.03979},
  }

  @Article{,
    journal = {Biometrika},
    title = {Non-parametric efficient causal mediation with
      intermediate confounders},
    author = {Iván Díaz and Nima S Hejazi and Kara E Rudolph and Mark J
      {van der Laan}},
    year = {2020},
    doi = {10.1093/biomet/asaa085},
    url = {https://arxiv.org/abs/1912.09936},
  }