PAPE {experiment}R Documentation

Estimation of the Population Average Prescription Effect in Completely Randomized Experiments

Description

This function estimates the Population Average Prescription Effect with and without a budget constraint. The details of the methods for this design are given in Imai and Li (2019).

Usage

PAPE(T, That, Y, plim = NA)

Arguments

T

The unit-level binary treatment receipt variable.

That

The unit-level binary treatment that would have been assigned by the individualized treatment rule.

Y

The outcome variable of interest.

plim

The maximum percentage of population that can be treated under the budget constraint. Should be a decimal between 0 and 1. Default is NA which assumes no budget constraint.

Value

A list that contains the following items:

pape

The estimated Population Average Prescription Effect.

sd

The estimated standard deviation of PAPE.

Author(s)

Michael Lingzhi Li, Operations Research Center, Massachusetts Institute of Technology mlli@mit.edu, http://mlli.mit.edu;

References

Imai and Li (2019). “Experimental Evaluation of Individualized Treatment Rules”,


[Package experiment version 1.2.1 Index]