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>.
