cvcrand: Efficient Design and Analysis of Cluster Randomized Trials

Constrained randomization by Raab and Butcher (2001) <doi:10.1002/1097-0258(20010215)20:3%3C351::AID-SIM797%3E3.0.CO;2-C> 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) <doi:10.1002/(SICI)1097-0258(19960615)15:11%3C1069::AID-SIM220%3E3.0.CO;2-Q>. Motivated from Li, et al. (2016) <doi:10.1002/sim.7410>, the package performs constrained randomization on the baseline values of cluster-level covariates and cluster permutation test on the individual-level outcome for cluster randomized trials.

Version: 0.0.1
Depends: R (≥ 3.3.1)
Imports: tableone
Suggests: knitr, rmarkdown
Published: 2017-11-28
Author: Hengshi Yu [aut, cre], John A. Gallis [aut], Fan Li [aut], Elizabeth L. Turner [aut]
Maintainer: Hengshi Yu <hengshi at umich.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: README
CRAN checks: cvcrand results

Downloads:

Reference manual: cvcrand.pdf
Vignettes: cvcrand package for the design and analysis of cluster randomized trials
Package source: cvcrand_0.0.1.tar.gz
Windows binaries: r-devel: cvcrand_0.0.1.zip, r-release: cvcrand_0.0.1.zip, r-oldrel: cvcrand_0.0.1.zip
OS X El Capitan binaries: r-release: cvcrand_0.0.1.tgz
OS X Mavericks binaries: r-oldrel: cvcrand_0.0.1.tgz

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