R: R Package for Designing and Analyzing Randomized Experiments

# R Package for Designing and Analyzing Randomized Experiments

## Documentation for package ‘experiment’ version 1.2.1

- DESCRIPTION file.

## Help Pages

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
ATEnocov | Estimation of the Average Treatment Effect in Randomized Experiments
ATOPnoassumption | Bounding the ATOP when some of the Outcome Data are Missing Under the Matched-Pairs Design
ATOPobs | Sensitivity analysis for the ATOP when some of the Outcome Data are Missing Under the Matched-Pairs Design in Observational Studies
ATOPsens | Sensitivity analysis for the ATOP when some of the Outcome Data are Missing Under the Matched-Pairs Design
AUPEC | Estimation of the unnormalized Area Under Prescription Evaluation Curve (AUPEC) in Completely Randomized Experiments
CACEcluster | Estimation of the Complier Average Causal Effects in Cluster-Randomized Experiments with Unit-level Noncompliance
CADErand | Randomization-based method for the complier average direct effect and the complier average spillover effect
CADEreg | Regression-based method for the complier average direct effect
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
PAPE | Estimation of the Population Average Prescription Effect in Completely Randomized Experiments
Randomize | Randomization of the Treatment Assignment for Conducting Experiments
randomize | Randomization of the Treatment Assignment for Conducting Experiments
seguro | Data from the Mexican universal health insurance program, Seguro Popular.