QT.crossover: Crossover Design in QT/QTc Studies without covariates

In TrialSize: R Functions for Chapter 3,4,6,7,9,10,11,12,14,15 of Sample Size Calculation in Clinical Research

Crossover Design in QT/QTc Studies without covariates

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.crossover(alpha, beta, pho, K, delta, gamma)

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

References

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

Examples

Example.15.1.3<-QT.crossover(0.05,0.2,0.8,3,0.5,0.002)
Example.15.1.3
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TrialSize documentation built on April 12, 2025, 2:01 a.m.