DESCRIPTION

Package: medoutcon
Title: Efficient Natural and Interventional Causal Mediation Analysis
Version: 0.2.2
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 (>= 1.4.3)
Suggests:
    testthat,
    knitr,
    rmarkdown,
    covr,
    Rsolnp,
    nnls,
    SuperLearner,
    glmnet,
    hal9001 (>= 0.4.1),
    speedglm,
    xgboost,
    ranger,
    arm
Remotes:
    github::tlverse/hal9001,
    github::tlverse/sl3@devel
License: MIT + file LICENSE
URL: https://github.com/nhejazi/medoutcon
BugReports: https://github.com/nhejazi/medoutcon/issues
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 7.3.1