cvcrand (0.0.2)

Efficient Design and Analysis of Cluster Randomized Trials.

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 cluster permutation test on the individual-level outcome for cluster randomized trials.

Maintainer: Hengshi Yu
Author(s): Hengshi Yu [aut, cre], John A. Gallis [aut], Fan Li [aut], Elizabeth L. Turner [aut]

License: GPL (>= 2)

Uses: tableone, knitr, rmarkdown

Released over 1 year ago.