Last data update: 2014.03.03
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rPowerSampleSize
Package: rPowerSampleSize
Type: Package
Title: Sample Size Computations Controlling the Type-II Generalized
Family-Wise Error Rate
Version: 1.0.1
Date: 2016-01-13
License: GPL (> 2)
LazyLoad: yes
Author: Pierre Lafaye de Micheaux, Benoit Liquet and Jeremie Riou
Maintainer: Pierre Lafaye de Micheaux <lafaye@dms.umontreal.ca>
Description: The significance of mean difference tests in clinical trials is established if at least r null hypotheses are rejected among m that are simultaneously tested. This package enables one to compute necessary sample sizes for single-step (Bonferroni) and step-wise procedures (Holm and Hochberg). These three procedures control the q-generalized family-wise error rate (probability of making at least q false rejections). Sample size is computed (for these single-step and step-wise procedures) in a such a way that the r-power (probability of rejecting at least r false null hypotheses, i.e. at least r significant endpoints among m) is above some given threshold, in the context of tests of difference of means for two groups of continuous endpoints (variables). Various types of structure of correlation are considered. It is also possible to analyse data (i.e., actually test difference in means) when these are available. The case r equals 1 is treated in separate functions that were used in Lafaye de Micheaux et al. (2014) <doi:10.1080/10543406.2013.860156>.
Depends: R (>= 2.10.0), mvtnorm, stats, ssanv, parallel
Packaged: 2016-01-13 16:32:08 UTC; lafaye
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2016-01-13 18:15:23
Install log
* installing to library '/home/ddbj/local/lib64/R/library'
* installing *source* package 'rPowerSampleSize' ...
** package 'rPowerSampleSize' successfully unpacked and MD5 sums checked
** R
** data
** preparing package for lazy loading
** help
*** installing help indices
converting help for package 'rPowerSampleSize'
finding HTML links ... done
Psirmd html
Psirms html
Psirmu html
bonferroni.1m.ssc html
complexity html
data.sim html
df.compute html
global.1m.analysis html
global.1m.ssc html
indiv.1m.analysis html
indiv.1m.ssc html
indiv.analysis html
indiv.rm.ssc html
matrix.type.compute html
montecarlo html
plot.rPower html
rPowerSampleSize-package html
** building package indices
** testing if installed package can be loaded
* DONE (rPowerSampleSize)
Making 'packages.html' ... done
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