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-oldrel (arm64): ivdesign_0.1.0.tgz, r-release (x86_64): ivdesign_0.1.0.tgz, r-oldrel (x86_64): ivdesign_0.1.0.tgz

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