| fwer_critical {PlatformDesign} | R Documentation |
Calculate the critical value and the marginal type-I error rate
Description
Calculate the critical value and the marginal type-I error rate given the number of experimental arms, the family-wise type I error rate and the correlation matrix of the z-statistics.
Usage
fwer_critical(ntrt, fwer, corMat, seed = 123)
Arguments
ntrt |
the number of experimental arms in the trial |
fwer |
the family-wise error rate (FWER) to be controlled, default to be the same throughout the trial |
corMat |
the correlation matrix of the Z-test statistics |
seed |
an integer used in random number generation for numerically evaluating integration, default = 123 |
Details
Use the number of experimental arms, the family-wise type I error rate and the correlation matrix of the Z-test statistics to calculate the marginal type I error rate and the critical value.
Value
pairwise_alpha the marginal type-I error rate for the comparison
between any of the experimental arm and its corresponding control
critical_val, the critical value for the comparison between any of
the experimental arm and the corresponding controls
Other values returned are inputs.
Author(s)
Xiaomeng Yuan, Haitao Pan
References
Dunnett, C. W. (1955). A multiple comparison procedure for comparing
several treatments with a control. Journal of the American Statistical
Association, 50(272), 1096-1121.
Examples
corMat1 <- cor.mat(K=2, M = 2, n=107, n0=198, n0t = 43)$cormat
fwer_critical(ntrt=4, fwer=0.025, corMat=corMat1)
#
#$ntrt
#[1] 4
#
#$fwer
#[1] 0.025
#
#$corMat
# [,1] [,2] [,3] [,4]
#[1,] 1.0000000 0.3508197 0.2746316 0.2746316
#[2,] 0.3508197 1.0000000 0.2746316 0.2746316
#[3,] 0.2746316 0.2746316 1.0000000 0.3508197
#[4,] 0.2746316 0.2746316 0.3508197 1.0000000
#
#$pairwise_alpha
#[1] 0.006657461
#
#$critical_val
#[1] 2.475233