Package: evalITR
Title: Evaluating Individualized Treatment Rules
Version: 1.1.0
Date: 2026-09-06
Authors@R: c(
    person("Michael Lingzhi", "Li", , "mili@hbs.edu", role = c("aut", "cre")),
    person("Kosuke", "Imai", , "imai@harvard.edu", role = "aut"),
    person("Jialu", "Li", , "jialu_li@g.harvard.edu", role = "ctb"),
    person("Xiaolong", "Yang", , "xiaolong_yang@g.harvard.edu", role = "ctb")
  )
Maintainer: Michael Lingzhi Li <mili@hbs.edu>
Description: Provides various statistical methods for evaluating
        Individualized Treatment Rules under randomized data. The
        provided metrics include Population Average Value (PAV),
        Population Average Prescription Effect (PAPE), Area Under
        Prescription Effect Curve (AUPEC). It also provides the tools
        to analyze Individualized Treatment Rules under budget
        constraints. Detailed reference in Imai and Li (2023)
        <doi:10.1080/01621459.2021.1923511>.
License: GPL (>=2)
URL: https://github.com/MichaelLLi/evalITR,
        https://michaellli.github.io/evalITR/,
        https://jialul.github.io/causal-ml/
BugReports: https://github.com/MichaelLLi/evalITR/issues
Depends: dplyr (>= 1.0), MASS (>= 7.0), Matrix (>= 1.0), quadprog (>=
        1.0), R (>= 3.5.0), stats
Imports: caret, cli, e1071, furrr, gbm, ggdist, ggplot2, ggthemes,
        glmnet, grf, haven, purrr, rlang, rpart, scales, bartCause,
        SuperLearner
Suggests: doParallel, knitr, rmarkdown, testthat, bartMachine,
        elasticnet, randomForest, spelling
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.3
Language: en-US
Config/pak/sysreqs: make libicu-dev libx11-dev zlib1g-dev
Repository: https://michaellli.r-universe.dev
Date/Publication: 2026-09-08 01:42:42 UTC
RemoteUrl: https://github.com/michaellli/evalitr
RemoteRef: HEAD
RemoteSha: 3117d593bf6dd36c1e6a6cab1c4aac80abe4bc68
NeedsCompilation: no
Packaged: 2026-10-08 07:59:05 UTC; root
Author: Michael Lingzhi Li [aut, cre],
  Kosuke Imai [aut],
  Jialu Li [ctb],
  Xiaolong Yang [ctb]