R: Sample size computation with an individual testing procedure...
indiv.1m.ssc
R Documentation
Sample size computation with an individual testing procedure in the context of multiple continuous endpoints
Description
This function computes the sample size with an individual testing procedure in the
context of multiple continuous endpoints. This method, based on the
Union-Intersection testing procedure, allows one to take into account
the correlation between the different endpoints in the computation of the sample size.
Usage
indiv.1m.ssc(method, ES, cor, power = 0.8, alpha = 0.05, alternative =
"two.sided", tol = 1e-04, maxiter = 1000, tol.uniroot = 1e-04)
Arguments
method
description of the covariance matrix estimation. Two
choices are possible: "Unknown" (normality assumption and unknown
covariance matrix) and "Asympt" (asymptotic context).
ES
vector indicating the values of the effect size. The definition of the effect size is presented in the "Details" section.
cor
matrix indicating the correlation matrix between the endpoints.
power
value which corresponds to the chosen power.
alpha
value which correponds to the chosen Type-I error rate bound.
alternative
character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less".
tol
the desired accuracy (convergence tolerance) for our algorithm.
maxiter
maximum number of iterations.
tol.uniroot
desired accuracy (convergence tolerance) for the
uniroot.integer function.
Details
ES: The effect size definition parameter for the k^{th} endpoint is defined as frac{μ^{T}_{k}-μ^{C}_{k}}{σ^{*}_{k}}, where σ^{*}_{k} refers to the standard deviation
of the population from which the different treatment groups were taken
and μ^{T}_{k}-μ^{C}_{k} is the true mean difference between the test and the control group for the k^{th} group. We consider that: σ^{*}_{k}=frac{σ^{2}_{k,T}+σ^{2}_{k,C}}{2}.
Value
Adjusted Type-I error rate
adjusted Type-I error rate.
Sample size
the required sample size.
Author(s)
P. Lafaye de Micheaux, B .Liquet and J .Riou
References
Lafaye de Micheaux P., Liquet B., Marque S., Riou J. (2014). Power and
Sample Size Determination in Clinical Trials With Multiple Primary
Continuous Correlated Endpoints, Journal of
Biopharmaceutical Statistics, 24, 378–397.