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 clustered permutation test on the individual-level outcomes for cluster randomized trials.
Version: |
0.1.0 |
Depends: |
R (≥ 3.4.0) |
Imports: |
tableone |
Suggests: |
knitr, rmarkdown |
Published: |
2020-04-13 |
Author: |
Hengshi Yu [aut, cre],
Fan Li [aut],
John A. Gallis [aut],
Elizabeth L. Turner [aut] |
Maintainer: |
Hengshi Yu <hengshi at umich.edu> |
License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: |
no |
Materials: |
NEWS |
CRAN checks: |
cvcrand results |
Documentation:
Downloads:
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