Package: medoutcon
Title: Efficient Natural and Interventional Causal Mediation Analysis
Version: 0.2.4
Authors@R: c(
    person("Nima", "Hejazi", email = "nh@nimahejazi.org",
           role = c("aut", "cre", "cph"),
           comment = c(ORCID = "0000-0002-7127-2789")),
    person("Iván", "Díaz", email = "ild2005@med.cornell.edu",
           role = "aut",
           comment = c(ORCID = "0000-0001-9056-2047")),
    person("Kara", "Rudolph", email = "kr2854@cumc.columbia.edu",
           role = "aut",
           comment = c(ORCID = "0000-0002-9417-7960")),
    person("Philippe", "Boileau", email = "philippe_boileau@berkeley.edu",
           role = "ctb",
           comment = c(ORCID = "0000-0002-4850-2507")),
    person("Mark", "van der Laan", email = "laan@berkeley.edu",
           role = c("ctb", "ths"),
           comment = c(ORCID = "0000-0003-1432-5511"))
  )
Maintainer: Nima Hejazi <nh@nimahejazi.org>
Description: Efficient estimators of interventional (in)direct effects
        in the presence of mediator-outcome confounding affected by
        exposure. The effects estimated allow for the impact of the
        exposure on the outcome through a direct path to be
        disentangled from that through mediators, even in the presence
        of intermediate confounders that complicate such a
        relationship. Currently supported are non-parametric efficient
        one-step and targeted minimum loss estimators based on the
        formulation of Díaz, Hejazi, Rudolph, and van der Laan (2020)
        <doi:10.1093/biomet/asaa085>. Support for efficient estimation
        of the natural (in)direct effects is also provided, appropriate
        for settings in which intermediate confounders are absent. The
        package also supports estimation of these effects when the
        mediators are measured using outcome-dependent two-phase
        sampling designs (e.g., case-cohort).
Depends: R (>= 3.2.0)
Imports: stats, data.table, assertthat, tibble, dplyr, zeallot, scales,
        stringr, origami (>= 1.0.3), glm2, sl3 (>= 1.4.5)
Suggests: testthat, knitr, rmarkdown, covr, Rsolnp, nnls, SuperLearner,
        glmnet, hal9001 (>= 0.4.6), speedglm, xgboost, ranger, arm
Remotes: github::tlverse/hal9001, github::tlverse/sl3
License: MIT + file LICENSE
URL: https://github.com/nhejazi/medoutcon
BugReports: https://github.com/nhejazi/medoutcon/issues
Encoding: UTF-8
VignetteBuilder: knitr
RoxygenNote: 7.3.1
Config/pak/sysreqs: cmake libglpk-dev make libicu-dev libuv1-dev
        libxml2-dev
Repository: https://ictml-project.r-universe.dev
Date/Publication: 2025-07-07 18:25:49 UTC
RemoteUrl: https://github.com/nhejazi/medoutcon
RemoteRef: HEAD
RemoteSha: e40d519cce0e674e4a2f1ba853c6d32908c7f9b0
NeedsCompilation: no
Packaged: 2026-06-05 07:22:20 UTC; root
Author: Nima Hejazi [aut, cre, cph] (ORCID:
    <https://orcid.org/0000-0002-7127-2789>),
  Iván Díaz [aut] (ORCID: <https://orcid.org/0000-0001-9056-2047>),
  Kara Rudolph [aut] (ORCID: <https://orcid.org/0000-0002-9417-7960>),
  Philippe Boileau [ctb] (ORCID: <https://orcid.org/0000-0002-4850-2507>),
  Mark van der Laan [ctb, ths] (ORCID:
    <https://orcid.org/0000-0003-1432-5511>)