PowerTOST (version 1.2-09)

exppower.TOST: 'Expected' power of TOST procedure

Description

Calculates the so-called 'expected' power according to Julious for a variety of study designs used in bioequivalence studies.

Usage

exppower.TOST(alpha = 0.05, logscale=TRUE, theta0, theta1, theta2,  
              CV, dfCV, n, design = "2x2", robust=FALSE)

Arguments

alpha

Level of significance. Commonly set to 0.05.

logscale

Should the data used on log-transformed or on original scale? TRUE or FALSE. Defaults to TRUE.

theta0

'True' or assumed bioequivalence ratio or difference. Typically set to 0.95 (default if missing) if logscale=TRUE. Defaults to 0.05 if logscale=FALSE.

theta1

Lower bioequivalence limit as ratio if logscale=TRUE or as difference. Can be missing. Defaults then to 0.8 if logscale=TRUE or to -0.2 if logscale=FALSE.

theta2

Upper bioequivalence limit as ratio if logscale=TRUE or as difference. If not given theta2 will be calculated as 1/theta1 if logscale=TRUE, else as -theta1.

CV

Coefficient of variation as ratio.

dfCV

Degrees of freedom for the CV (error/residual degree of freedom).

n

Number of subjects under study. Is total number if given as scalar, else number of subjects in the (sequence) groups. In the latter case the length of n vector has to be equal to the number of (sequence) groups.

design

Character string describing the study design. See known.designs() for designs covered in this package.

robust

Defaults to FALSE. Set to TRUE will use the degrees of freedom according to the 'robust' evaluation (aka Senn's basic estimator). These df are calculated as n-seq. See known.designs()$df2 for designs covered in this

Value

• Value of expected power according to the input.

Details

This function calculates the so-called 'expected' power based on S.A. Julious taking into account that usually the CV is not known but estimated from a previous study / studies with an uncertainty. See references.

References

S.A. Julious, R.J. Owen "Sample size calculations for clinical studies allowing for uncertainty in variance" Pharmaceutical Statistics (2006), 5, 29-37 S.A. Julious "Sample sizes for Clinical Trials" CRC Press, Chapman & Hall 2010

See Also

expsampleN.TOST, power.TOST

Examples

# expected power for a 2x2 crossover
# CV 30\% known from a pilot study with 12 subjects (-> dfCV=10)
# using all the defaults for other parameters
# should give: [1] 0.7359771
exppower.TOST(CV=0.3, dfCV=10, n=40)

# Compare this to the usual power (CV known, "carved in stone")
# gives: [1] 0.8158453
power.TOST(CV=0.3, n=40)