sample size in bioequivalence studies [Power / Sample Size]

posted by daryazyatina – Ukraine, 2017-08-03 12:58 (2450 d 16:29 ago) – Posting: # 17650
Views: 18,840

Hi ElMaestro,

❝ Good choice :-D


Thank you

❝ Can you tell what your design is and which values you want to plug in for the calculation? If the difference is 2 or 4 subjects, then so be it, subtle differences in approximation may account for that. If the difference is 46 or something then I'd wonder, too. I am sure there is an explanation and that your confidence in the powerTOST package can easily be restored.


For comparison, I use all the standard properties. Design 2x2, confidence intervals 0.8 - 1.25, power 0.8, alpha 0.05.
The only thing about what I'm not sure is CV. Because in formula that I used this is intra-subject variability, but in PowerTOST() this is coefficient of variation as ratio. In calculations in both cases I used СV - 0.3.

And this is results from sampleN.TOST()
sampleN.TOST(logscale = TRUE, CV = 0.3, details = TRUE)
+++++++++++ Equivalence test - TOST +++++++++++
            Sample size estimation
-----------------------------------------------
Study design:  2x2 crossover
log-transformed data (multiplicative model)

alpha = 0.05, target power = 0.8
BE margins = 0.8 ... 1.25
True ratio = 0.95,  CV = 0.3

Sample size (total)
 n     power
40   0.815845

The sample size by the formula I used:

n=28

❝ Apart from that you are of course right if you intended to hint that the author of the power.TOST family of R functions is a dubious character.


:-D:-D:-D

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