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”,