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cvcrand (version 0.1.1)

Efficient Design and Analysis of Cluster Randomized Trials

Description

Constrained randomization by Raab and Butcher (2001) is suitable for cluster randomized trials (CRTs) with a small number of clusters (e.g., 20 or fewer). The procedure of constrained randomization is based on the baseline values of some cluster-level covariates specified. The intervention effect on the individual outcome can then be analyzed through clustered permutation test introduced by Gail, et al. (1996) . Motivated from Li, et al. (2016) , the package performs constrained randomization on the baseline values of cluster-level covariates and clustered permutation test on the individual-level outcomes for cluster randomized trials.

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Install

install.packages('cvcrand')

Monthly Downloads

229

Version

0.1.1

License

GPL (>= 2)

Maintainer

Hengshi Yu

Last Published

September 17th, 2023

Functions in cvcrand (0.1.1)

cvcrand

cvcrand: a package for efficient design and analysis of cluster randomized trials
Dickinson_outcome

Simulated individual-level binary outcome and baseline variables for study 1 in Dickinson et al (2015)
Dickinson_design

Raw county-level variables for study 1 in Dickinson et al (2015)
cptest

Clustered permutation test for cluster randomized trials
cvrcov

Covariate-by-covariate constrained randomization for cluster randomized trials
cvrall

Covariate-constrained randomization for cluster randomized trials