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rPowerSampleSize (version 1.0.2)

Sample Size Computations Controlling the Type-II Generalized Family-Wise Error Rate

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) .

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Version

Install

install.packages('rPowerSampleSize')

Monthly Downloads

204

Version

1.0.2

License

GPL (> 2)

Maintainer

P. de Micheaux

Last Published

May 10th, 2018

Functions in rPowerSampleSize (1.0.2)

Psirmu

Computation of power for step-up (Hochberg) procedure.
bonferroni.1m.ssc

Sample Size Computation with Single Step Bonferroni Method in the Context of Multiple Continuous Endpoints.
indiv.1m.ssc

Sample size computation with an individual testing procedure in the context of multiple continuous endpoints
indiv.analysis

Data analysis using an individual testing procedure controlling the q-gFWER in the context of \(m\) multiple continuous endpoints
Psirmd

Computation of power for step-down (Holm) procedure.
Psirms

Computation of power for single step (Bonferroni) procedure.
rPowerSampleSize-package

Sample Size Computation and Data Analysis in the context of multiple continuous endpoints in clinical trials.
global.1m.ssc

Sample Size Computation Based on a Global Procedure in the Context of Multiple Continuous Endpoints
indiv.1m.analysis

Data analysis with an individual testing procedure in the context of multiple continuous endpoints
indiv.rm.ssc

Sample size determination in the context of multiple continuous endpoints with a control of the q-gFWER, for a given value of r-power (generalized disjunctive power).
matrix.type.compute

Computation of matrix type
complexity

Computation of the complexity of the numerical computations.
data

Simulated data
plot.rPower

Plot of an rPower object
montecarlo

Monte carlo computation of power.
df.compute

Computation of degrees of freedom.
global.1m.analysis

Data analysis with a global method in the context of multiple continuous endpoints