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README.Rmd
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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>")
```
## evalITR [![CRAN_Status_Badge](http://www.r-pkg.org/badges/version/evalITR)](https://cran.r-project.org/package=evalITR) ![CRAN downloads](http://cranlogs.r-pkg.org/badges/grand-total/evalITR)
<!-- badges: start -->
<!-- badges: end -->
```{r pic1, echo=FALSE}
knitr::include_graphics("man/figures/README-manual.png")
```
R package evalITR provides various statistical methods for estimating
and evaluating Individualized Treatment Rules under randomized data. The
provided metrics include (1) population average prescriptive effect
`PAPE`; (2) population average prescriptive effect with a budget
constraint `PAPEp`; (3) population average prescriptive effect
difference with a budget constraint `PAPDp`; (4) and area under the
prescriptive effect curve `AUPEC`; (5) Grouped Average Treatment
Effects `GATEs`. The details of the methods for this design are given in [Imai and Li
(2023)](https://arxiv.org/abs/1905.05389) and
[Imai and Li](https://arxiv.org/abs/2203.14511).
Documentation and website: https://michaellli.github.io/evalITR/