cfperformance/DESCRIPTION at main · boyercb/cfperformance · GitHub

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Package: cfperformance
Title: Counterfactual Prediction Model Performance Estimation
Version: 0.5.0
Authors@R: c(
    person("Christopher", "Boyer",
           email = "cboyer@hsph.harvard.edu",
           role = c("aut", "cre"),
           comment = c(ORCID = "0000-0003-0935-8722")),
    person("Issa", "Dahabreh",
           role = "aut",
           comment = c(ORCID = "0000-0002-1195-1850")),
    person("Jon", "Steingrimsson",
           role = "aut",
           comment = c(ORCID = "0000-0002-8284-8877"))
    )
Description: Provides methods for estimating model performance measures
    (mean squared error, area under the ROC curve, calibration) under
    hypothetical/counterfactual interventions. Implements conditional loss,
    inverse probability weighting, and doubly robust estimators from
    Boyer, Dahabreh & Steingrimsson (2025) <doi:10.1002/sim.70287>.
    These methods are essential when prediction models will be deployed
    in settings where treatment policies differ from training, or when
    predictions support treatment decisions.
License: MIT + file LICENSE
URL: https://github.com/boyercb/cfperformance,
    https://boyercb.github.io/cfperformance/
BugReports: https://github.com/boyercb/cfperformance/issues
Depends:
    R (>= 4.0.0)
Imports:
    stats,
    graphics,
    grDevices,
    rlang (>= 1.0.0)
Suggests:
    MASS,
    mgcv,
    boot,
    ggplot2,
    glmnet,
    grf,
    knitr,
    patchwork,
    pROC,
    ranger,
    rmarkdown,
    SuperLearner,
    testthat (>= 3.0.0),
    WeightedROC,
    xgboost
VignetteBuilder: knitr
Config/testthat/edition: 3
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2