sampleN.scABEL: Sample size estimation for BE decision via scaled (widened) BE acceptance limits

Description

This function performs the Sample size estimation for the BE decision via scaled (widened) BE acceptance limits based on simulations.

Usage

sampleN.scABEL(alpha = 0.05, targetpower = 0.8, theta0, theta1, theta2, CV, 
               design = c("2x3x3", "2x2x4", "2x2x3"), regulator = c("EMA", "FDA"), 
               nsims = 1e+05, nstart, print = TRUE, details = TRUE, setseed = TRUE)

Arguments

alpha

Type I error probability. Per convention mostly set to 0.05.

targetpower

Power to achieve at least. Must be >0 and

theta0

'True' or assumed bioequivalence ratio. Defaults to 0.95 if given explicitly.

theta1

Conventional lower ABE limit to be applied in the mixed procedure if CVsWR

theta2

Conventional upper ABE limit to be applied in the mixed procedure if CVsWR

Coefficient(s) of variation as ratio. If length(CV) = 1 the same CV is assumed for Test and Reference. If length(CV) = 2 the CV for Test must be given in CV[1] and for Reference in CV[2].

design

Design of the study to be planned. 2x3x3 is the partial replicate design (TRR|RTR|RRT). 2x2x3 is the 3-period replicate design (TRT|RTR). 2x2x4 is the full replicate design with 2 sequences and 4 periods. Defaults to design="2x3x3"

regulator

Regulatory body settings for the widening of the BE acceptance limits. Defaults to design="EMA".

nsims

Number of simulations to be performed to obtain the (empirical) power. The default value 100 000 = 1e+5 is usually sufficient. Consider to rise this value if theta0<=0.85 or="">=1.25. But see the warning section.

nstart

Set this to a start for the sample size search if a previous run failed. After reworking the start n in version 1.1-05 seldom needed.

If TRUE (default) the function prints its results.

details

If set to TRUE, the default, the steps during sample size search are shown.

setseed

Simulations are dependent on the starting point of the (pseudo) random number generator. To avoid differences in power for different runs a set.seed(123456) is issued if setseed=TRUE, the default.

Value

Returns now a data.frame with the input and sample size results. The "Sample size" column contains the total sample size. The "nlast" column contains the last n value. May be useful for restarting.

Warning

The sample size estimation for very extreme theta0 (<0.83 or="">1.21) may be very time consuming and will eventually also fail since the start values chosen are not really reasonable in that ranges. This is especially true in the range around CV = 0.3 and regulatory constant according to FDA. If you really need sample sizes in that range be prepared to restart the sample size estimation via the argument nstart. Since the dependence of power from n is very flat in the mentioned region you may also consider to adapt the number of simulations not to tap in the simulation error trap. See also the Warning section of the function power.scABEL() concerning the power value agreement to those obtained from simulations via subject data.

Details

The simulations are done via the distributional properties of the statistical quantities necessary for deciding BE based on widened ABEL. For more details see a document in the doc subdirectory of the package.

References

Laszlo Tothfalusi and Laszlo Endrenyi "Sample Sizes for Designing Bioequivalence Studies for Highly Variable Drugs" J. Pharm. Pharmaceut. Sci. (www.cspsCanada.org) 15(1) 73 - 84, 2011

Examples

Run this code

# using all the defaults:
# partial replicate design, targetpower=80\%,
# true assumed ratio = 0.95, 1E+5 simulated studies
# ABE limits, PE constraint 0.8 - 1.25
# EMA regulatory settings
sampleN.scABEL(CV=0.3)
# results in a sample size n=27, power=0.82566

# for the full replicate design, target power = 90\%
# true assumed ratio = 0.9, FDA regulatory settings
sampleN.scABEL(CV=0.4, targetpower=0.9, theta0=0.9, design="2x2x4", regulator="FDA")
# should result in a sample size n=30, power=0.9074

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