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experiment (version 1.2.1)

R Package for Designing and Analyzing Randomized Experiments

Description

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.

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Install

install.packages('experiment')

Monthly Downloads

315

Version

1.2.1

License

GPL (>= 2)

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Maintainer

Kosuke Imai

Last Published

April 12th, 2022

Functions in experiment (1.2.1)

ATOPobs

Sensitivity analysis for the ATOP when some of the Outcome Data are Missing Under the Matched-Pairs Design in Observational Studies
ATEnocov

Estimation of the Average Treatment Effect in Randomized Experiments
ATEbounds

Bounding the Average Treatment Effect when some of the Outcome Data are Missing
ATEcluster

Estimation of the Average Treatment Effects in Cluster-Randomized Experiments
AUPEC

Estimation of the unnormalized Area Under Prescription Evaluation Curve (AUPEC) in Completely Randomized Experiments
ATOPsens

Sensitivity analysis for the ATOP when some of the Outcome Data are Missing Under the Matched-Pairs Design
ATOPnoassumption

Bounding the ATOP when some of the Outcome Data are Missing Under the Matched-Pairs Design
CADEreg

Regression-based method for the complier average direct effect
CADErand

Randomization-based method for the complier average direct effect and the complier average spillover effect
CACEcluster

Estimation of the Complier Average Causal Effects in Cluster-Randomized Experiments with Unit-level Noncompliance
seguro

Data from the Mexican universal health insurance program, Seguro Popular.
randomize

Randomization of the Treatment Assignment for Conducting Experiments
PAPE

Estimation of the Population Average Prescription Effect in Completely Randomized Experiments
NoncompLI

Bayesian Analysis of Randomized Experiments with Noncompliance and Missing Outcomes Under the Assumption of Latent Ignorability
PAPD

Estimation of the Population Average Prescription Difference in Completely Randomized Experiments