ivdesign: Hypothesis Testing in Cluster-Randomized Encouragement Designs

An implementation of randomization-based hypothesis testing for three different estimands in a cluster-randomized encouragement experiment. The three estimands include (1) testing a cluster-level constant proportional treatment effect (Fisher's sharp null hypothesis), (2) pooled effect ratio, and (3) average cluster effect ratio. To test the third estimand, user needs to install 'Gurobi' (>= 9.0.1) optimizer via its R API. Please refer to <https://www.gurobi.com/documentation/9.0/refman/ins_the_r_package.html>.

Getting started

Package details

AuthorBo Zhang
MaintainerBo Zhang <bozhan@wharton.upenn.edu>
Package repositoryView on CRAN
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ivdesign documentation built on July 14, 2020, 5:07 p.m.