Description
Evaluating Individualized Treatment Rules.
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 (2019) <arXiv:1905.05389>.
README.md
evalITR 
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) and Imai and Li.
Documentation and website: https://michaellli.github.io/evalITR/