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>.

Version: 0.1.0
Depends: R (≥ 2.10)
Imports: stats
Suggests: gurobi, Matrix
Published: 2020-07-14
Author: Bo Zhang
Maintainer: Bo Zhang <bozhan at wharton.upenn.edu>
License: GPL-3
NeedsCompilation: no
CRAN checks: ivdesign results

Documentation:

Reference manual: ivdesign.pdf

Downloads:

Package source: ivdesign_0.1.0.tar.gz
Windows binaries: r-devel: ivdesign_0.1.0.zip, r-release: ivdesign_0.1.0.zip, r-oldrel: ivdesign_0.1.0.zip
macOS binaries: r-release (arm64): ivdesign_0.1.0.tgz, r-release (x86_64): ivdesign_0.1.0.tgz, r-oldrel: ivdesign_0.1.0.tgz

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