cvcrand: Efficient Design and Analysis of Cluster Randomized Trials
Version 0.0.1

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.

Package details

AuthorHengshi Yu [aut, cre], John A. Gallis [aut], Fan Li [aut], Elizabeth L. Turner [aut]
Date of publication2017-11-28 19:06:15 UTC
MaintainerHengshi Yu <[email protected]>
LicenseGPL (>= 2)
Version0.0.1
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("cvcrand")

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cvcrand documentation built on Nov. 29, 2017, 1:02 a.m.