PlatformDesign (version 2.1.4)

fwer_critical: 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)

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.

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

Author

Xiaomeng Yuan, Haitao Pan

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.

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