Title: Tools for Clustering High-Dimensional Data
Description: Tools for clustering high-dimensional data.
In particular, it contains the methods described in
Imports: Rcpp (>= 1.0.7), stats, mclust, Ckmeans.1d.dp, cluster

Package: clusterPower
Version: 0.1
Date: 2011-04-28
Title: Power calculations for cluster-randomized crossover trials
Author: Nicholas G. Reich <nick.reich@gmail.com>, Daniel Obeng
<dobeng@gmail.com>
Maintainer: Nicholas G. Reich <nick.reich@gmail.com>
License: GPL (>= 2)
Depends: lme4
Description: This package enables researchers to calculate power for
cluster-randomized crossover trials by employing a
simulation-based approach.  A particular study design is
specified, with fixed sample sizes for all clusters and an
assumed treatment effect, and the empirical power for that
study design is calculated by simulating hypothetical datasets.
Packaged: 2011-06-01 16:29:43 UTC; nick
Repository: CRAN
Date/Publication: 2011-06-02 05:34:42

Title: Power calculations for cluster-randomized and cluster-randomized

Author: Nicholas G. Reich <nick@schoolph.umass.edu>, Daniel Obeng <dobeng@gmail.com>
Maintainer: Nicholas G. Reich <nick@schoolph.umass.edu>
Description: This package enables researchers to calculate power for cluster-randomized crossover trials by employing a simulation-based approach.  A particular study design is specified, with fixed sample sizes for all clusters and an assumed treatment effect, and the empirical power for that study design is calculated by simulating hypothetical datasets.

Title: Power Calculations for Cluster-Randomized and Cluster-Randomized
person("Ken", "Kleinman", email = "ken.kleinman@gmail.com", rol = c("aut","cre")),
person("Jon", "Moyer", email = "jon.moyer@gmail.com", rol = c("aut")),
person("Nicholas", "Reich", email = "nick@schoolph.umass.edu", rol = c("aut")),
person("Daniel", "Obeng", email = "dobeng@gmail.com", rol = c("ctb"))
Description: Calculate power for cluster randomized trials (CRTs) that compare two means, two proportions, or two counts using closed-form solutions. In addition, calculate power for cluster randomized  crossover trials using Monte Carlo methods. For more information, see Reich et al. (2012) <doi:10.1371/journal.pone.0035564>.
Packaged: 2017-09-04 18:06:57 UTC; kkleinman