TrialSize (version 1.4)

QT.PK.crossover: Crossover Design in QT/QTc Studies with PK response as covariate

Description

Ho: \(\mu_1 -\mu_2 = 0 \)

Ha: \(\mu_1 -\mu_2 = d \)

The test is finding the treatment difference in QT interval for crossover design. d is not equal to 0, which is the difference of clinically importance.

Usage

QT.PK.crossover(alpha, beta, pho, K, delta, gamma, v1, v2, tau1, tau2)

Arguments

alpha

significance level

beta

power = 1-beta

pho

pho=between subject variance \(\sigma^{2}_{s}\)/(between subject variance \(\sigma^2_s\)+within subject variance \(\sigma^2_e\))

K

There are K recording replicates for each subject.

delta

\(\sigma^2=\sigma^2_s+\sigma^2_e\). d is the difference of clinically importance. \(\delta = d/\sigma \)

gamma

\(\sigma^2_p\) is the extra variance from the random period effect for the crossover design. \(\gamma=\sigma^2_p/\sigma^2\)

v1

sample mean for group 1

v2

sample mean for group 2

tau1

sample variance for group 1

tau2

sample variance for group 2

References

Chow SC, Shao J, Wang H. Sample Size Calculation in Clinical Research. New York: Marcel Dekker, 2003

Examples

# NOT RUN {
Example.15.1.4.2<-QT.PK.crossover(0.05,0.2,0.8,3,0.5,0.002,1,1,4,5)
Example.15.1.4.2
# 29

# }