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message: 'To cite package "evalITR" in publications use:'
type: software
title: 'evalITR: Evaluating Individualized Treatment Rules'
version: 1.0.0
doi: 10.32614/CRAN.package.evalITR
identifiers:
- type: url
  value: https://jialul.github.io/causal-ml/
abstract: 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 (2019) <arXiv:1905.05389>.
authors:
- family-names: Li
  given-names: Michael Lingzhi
  email: mili@hbs.edu
- family-names: Imai
  given-names: Kosuke
  email: imai@harvard.edu
repository: https://michaellli.r-universe.dev
repository-code: https://github.com/MichaelLLi/evalITR
commit: 50d68e9c985738aa7a1cb982545bba3255390482
url: https://michaellli.github.io/evalITR/
date-released: '2023-08-20'
contact:
- family-names: Li
  given-names: Michael Lingzhi
  email: mili@hbs.edu