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evalITR

R package evalITR 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.

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Install

install.packages('evalITR')

Monthly Downloads

263

Version

0.1.0

License

GPL (>= 2)

Issues

3

Pull Requests

4

Stars

14

Forks

4

Maintainer

Michael Li

Last Published

February 20th, 2020

Functions in evalITR (0.1.0)

AUPECcv

Estimation of the Area Under Prescription Evaluation Curve (AUPEC) in Randomized Experiments Under Cross Validation
PAVcv

Estimation of the Population Average Value in Randomized Experiments Under Cross Validation
PAPEcv

Estimation of the Population Average Prescription Effect in Randomized Experiments Under Cross Validation
PAPDcv

Estimation of the Population Average Prescription Difference in Randomized Experiments Under Cross Validation
PAPD

Estimation of the Population Average Prescription Difference in Randomized Experiments
PAPE

Estimation of the Population Average Prescription Effect in Randomized Experiments
PAV

Estimation of the Population Average Value in Randomized Experiments
AUPEC

Estimation of the Area Under Prescription Evaluation Curve (AUPEC) in Randomized Experiments