PAPE

The unit-level binary treatment receipt variable.

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

That

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.

plim

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).

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.

PAPE: Estimation of the Population Average Prescription Effect in Completely Randomized Experiments

Description

Usage

Arguments

Value

References