PAPD

The unit-level binary treatment receipt variable.

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

Thatfp

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

Thatgp

The maximum percentage of population that can be treated under the
budget constraint. Should be a decimal between 0 and 1.

plim

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).

Evaluation

Provides various statistical methods for
designing and analyzing randomized experiments. One functionality
of the package is the implementation of randomized-block and
matched-pair designs based on possibly multivariate pre-treatment
covariates. The package also provides the tools to analyze various
randomized experiments including cluster randomized experiments,
two-stage randomized experiments, randomized experiments with
noncompliance, and randomized experiments with missing data.

PAPD: Estimation of the Population Average Prescription Difference in Completely Randomized Experiments

Description

Usage

Arguments

Value

References