DESCRIPTION

Package: stremr
Title: Streamlined Estimation for Static, Dynamic and Stochastic Treatment Regimes in Longitudinal Data
Version: 0.8.99
Authors@R: c(
    person("Oleg", "Sofrygin", role=c("aut", "cre"), email="oleg.sofrygin@gmail.com"),
    person(c("Mark", "J."), "van der Laan", role="aut", email="laan@berkeley.edu"),
    person("Romain", "Neugebauer", role="aut", email="Romain.S.Neugebauer@kp.org"))
Description: Analysis of longitudinal data with binary (time-to-event) or continuous outcomes.
    Estimates the mean counterfactual outcome or counterfactual survival under static, dynamic and
    stochastic interventions on treatment (exposure) and monitoring events over time.
    Adjusts for measured time-varying confounding and informative right-censoring.
    Possible estimators are: bounded IPW, hazard-based IPW (NPMSM), hazard-based IPW MSM, 
    direct plug-in for longitudinal G-formula (GCOMP), long-format TMLE and infinite-dimensional 
    TMLE (iTMLE).
    Use data-adaptive estimation with machine learning algorithms implemented in
    xgboost or h2o (Extreme Gradient Boosting, Random Forest, Deep Neural Nets).
    Perform model selection with V-fold cross-validation.
    The exposure, monitoring and censoring variables can be binary,
    categorical or continuous. Each can be multivariate (e.g., can use more than one
    column of dummy indicators for different censoring events).
    The input data needs to be in long format.
URL: https://github.com/osofr/stremr
BugReports: https://github.com/osofr/stremr/issues
SystemRequirements: pandoc (http://pandoc.org) for generating and exporting
    markdown reports to other formats.
Depends:
    R (>= 3.2.1)
Imports:
    assertthat,
    condensier,
    data.table,
    dplyr,
    gridisl,
    magrittr,
    methods,
    origami,
    pander,
    purrr,
    R6,
    rmarkdown,
    speedglm,
    sl3,
    stats,
    tibble,
    tidyr,
    zoo
Suggests:
    bibtex,
    doParallel,
    foreach,
    ggiraph,
    ggplot2,
    glmnet,
    h2o,
    knitr,
    RefManageR,
    Rsolnp,
    RUnit,
    SuperLearner,
    testthat,
    mockery,
    xgboost
Remotes:
    github::jeremyrcoyle/sl3,
    github::jeremyrcoyle/origami@old-stable,
    github::osofr/condensier,
    github::osofr/gridisl
License: MIT + file LICENSE
LazyData: true
RoxygenNote: 7.1.1