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 singlestep (Bonferroni) and stepwise procedures (Holm and Hochberg). These three procedures control the qgeneralized familywise error rate (probability of making at least q false rejections). Sample size is computed (for these singlestep and stepwise procedures) in a such a way that the rpower (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)
Package details 


Author  Pierre Lafaye de Micheaux, Benoit Liquet and Jeremie Riou 
Date of publication  20180510 12:16:42 UTC 
Maintainer  Pierre Lafaye de Micheaux <[email protected]> 
License  GPL (> 2) 
Version  1.0.2 
Package repository  View on CRAN 
Installation 
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