Bioequivalence and Bioavailability Forum

Gentleman!

❝ What I am thinking at present is this: For Potvin method B/C/D we use the CV from stage 1 in the sample size estimation for stage 2, but we do not use the observed T/R; in stead we use fixed T/R=0.9 or 0.95 etc.

Yes, since the framework is not fully adaptive (taking estimated variance + effect size into account) but only a sample size re-estimation. Full adaptive designs are nice if the sample size is really (!) large. If we have two estimates (T/R and CV) from the small sample sizes in BE the penalty might be terrible. The distribution of total sample sizes in B/C/D is already highly skewed to the right. In some preliminary sims I got awful results – especially if the first stage was relatively small (compared to a fixed design of the same CV) and the T/R was by chance >±10% from 1. IMHO, B/C/D (fixed α_adj.) no way. Would be interesting how the ol’ pirate’s framework performs in such a situation.

❝ On the other hand we do use observed T/R when we test for BE at both stages.

Sure.

❝ So, let's be consequent and propose we will use the fixed T/R of 0.90 or 0.95 for evaluation of BE at stage 1

What if a study passes (actual T/R) with 0.05 or 0.0294 (C), 0.0294 (B), or 0.0280 (D) in stage 1 and fails with T/R 0.95 (B/C) or 0.90 (D)? Following the same logic should we reject a conventional fixed sample study which was planned for T/R 0.95, CV somefink (T/R <0.95 – but passes due to a lower CV)?

❝ … and dimensioning of st. 2.

Well, that’s exactly what B/C/D does, IMHO.

❝ To do this we must then find the maximum likelihood of the anova RMSE (s, CV) given the model, the fixed T/R ratio and the observations.

– again.