Package: evalITR
Version: 0.1.0
Date: 2020-01-28
Title: Evaluating Individualized Treatment Rules
Authors@R: c(
  person("Michael Lingzhi", "Li", , "mlli@mit.edu", c("aut", "cre")),
  person("Kosuke", "Imai", , "imai@harvard.edu", c("aut"))
  )
Maintainer: Michael Lingzhi Li <mlli@mit.edu>
Depends: stats, R (>= 3.5.0)
Description: A collection of statistical methods for evaluating individualized treatment rules under randomized data. The provided metrics include PAV (Population Average Value), PAPE (Population Average Prescription Effect), and AUPEC (Area Under Prescription Effect Curve). It also provides the tools to analyze individualized treatment rules under budget constraints. Imai and Li (2019) <arXiv:1905.05389>.
License: GPL (>= 2)
URL: https://github.com/MichaelLLi/evalITR
BugReports: https://github.com/MichaelLLi/evalITR/issues
RoxygenNote: 7.0.2
Suggests: testthat
NeedsCompilation: no
Packaged: 2020-02-10 16:55:51 UTC; Michael
Author: Michael Lingzhi Li [aut, cre],
  Kosuke Imai [aut]
Repository: CRAN
Date/Publication: 2020-02-20 09:10:05 UTC
