Bioequivalence and Bioavailability Forum

Dear earlybird!

❝ I have done a sample size estimation with FARTSSIE for example FDA, partial replicate, 80% power, ratio 90%, CV = 35% this result in N= 48. Whereas when I look in Table A3 I got N=37. Substantial less subjects!

Cave! FARTSSIE contains sW0=0.294 as regulatory constant.
But Haidar et.al had proposed sW0=0.25, switching to scaled ABE also at CV=30% (corresponds to sWR=0.294). sW0=0.294 corresponds to k=0.76..., the EMA regulatory setting. You can see this if you choose consecutive the FDA approach and the EMA approach from the drop-down box. Both methods give the same sample size.

With sW0=0.25 you will get N=29 from FARTSSIE with your settings.

Comparison to the simulated results is difficult because FARTSSSIE obviously calculates the sample size the usual way but with widened acceptance ranges (ABEL with FDA regulatory constant), whereas the simulations had used the scaled ABE criterion directly (upper 95% CI of the linearised criterion <0).
Moreover FARTSSIE uses the formulas for a balanced classical 2x2 crossover (!) correcting the obtained sample size to 0.75*n(2x2) for a 3-period replicate design with 2 sequences (not partial replicate) and the approximation of the power via non-central t-distribution. Approximate approximations .

PowerTOST comes out with:
require(PowerTOST)
sampleN.TOST(CV=0.35, theta0=0.9, theta1=exp(-0.893*CV2se(0.35)), design="2x3x3", details=TRUE, method="exact")

+++++++++++ Equivalence test - TOST +++++++++++
            Sample size estimation
-----------------------------------------------
Study design:  partial replicate (2x3x3)
Design characteristics:
df = 2*n-3, design const. = 1.5, step = 3

log-transformed data (multiplicative model)

alpha = 0.05, target power = 0.8
BE margins        = 0.7381817 ... 1.35468
Null (true) ratio = 0.9,  CV = 0.35

Sample size search (ntotal)
 n     power
27   0.786584
30   0.824086

Exact power calculation with Owen's Q functions.

❝ Somehow strange for me, as I would guess the more constraints the higher the sample size.

Right guess if you look at the corrected result .