PAPD: Estimation of the Population Average Prescription Difference...

In experiment: R Package for Designing and Analyzing Randomized Experiments

Estimation of the Population Average Prescription Difference in Completely Randomized Experiments

Description

This function estimates the Population Average Prescription Difference with a budget constraint. The details of the methods for this design are given in Imai and Li (2019).

Usage

PAPD(T, Thatfp, Thatgp, Y, plim)

Arguments

T	The unit-level binary treatment receipt variable.
Thatfp	The unit-level binary treatment that would have been assigned by the first individualized treatment rule.
Thatgp	The unit-level binary treatment that would have been assigned by the second 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.

Value

A list that contains the following items:

papd	The estimated Population Average Prescription Difference
sd	The estimated standard deviation of PAPD.

Author(s)

Michael Lingzhi Li, Operations Research Center, Massachusetts Institute of Technology [e-mail], http://mlli.mit.edu;

References

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

experiment documentation built on April 13, 2022, 1:06 a.m.