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ivdesign  

Hypothesis Testing in Cluster-Randomized Encouragement Designs
View on CRAN: Click here


Download and install ivdesign package within the R console
Install from CRAN:
install.packages("ivdesign")

Install from Github:
library("remotes")
install_github("cran/ivdesign")

Install by package version:
library("remotes")
install_version("ivdesign", "0.1.0")



Attach the package and use:
library("ivdesign")
Maintained by
Bo Zhang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-07-14
Latest Update: 2020-07-14
Description:
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 .
How to cite:
Bo Zhang (2020). ivdesign: Hypothesis Testing in Cluster-Randomized Encouragement Designs. R package version 0.1.0, https://cran.r-project.org/web/packages/ivdesign. Accessed 22 Dec. 2024.
Previous versions and publish date:
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Complete documentation for ivdesign
Functions, R codes and Examples using the ivdesign R package
Some associated functions: ACER . PER . PER_CI . control_clusters . double_rank . double_rank_CI . encouraged_clusters . 
Some associated R codes: ACER.R . PER.R . PER_CI.R . control_clusters.R . double_rank.R . double_rank_CI.R . encouraged_clusters.R .  Full ivdesign package functions and examples
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