Bioequivalence and Bioavailability Forum

Dear Helmut!

❝ ❝ What if the CV comes out other than supposed in the planning?

❝

❝ Good point! In order to be protected against that sims should cover a realistic (!) range of CVs (and n₁ – drop outs!), not only the expected one. If the (mandatory?) a posteriori sim shows α_emp. >0.05, bad luck. If we go with a fixed sample design instead and the CV turns out to be higher than expected we may fail as well. Part of the game.

❝ But let’s simulate. Method B on steroids wo power,

❝ α_adj. 0.0380, but CV 35%.

❝            Ratio 1.25                 │             Ratio 0.95             


❝ ──────────────────────────────────────┼─────────────────────────────────────


❝                      % in    empiric  │                      % in   empiric
❝  n   (5%, 50%, 95%) stage 2     α     │  n   (5%, 50%, 95%) stage 2   1-β 


❝ 56.8  36   56   80   92.10   0.057127 │ 46.7  36   36   78   42.2   0.83226

❝ Ouch! Bad idea. ...

Got you!

❝ Now for the positive part. If one follows Method B, IMHO a posteriori simulations are not necessary if the study was planned with a n₁ corresponding to max. α_emp.. That would mean that we are already on ‘top of the ridge’. What could happen?

• Drop-outs: We go left in the plot and see the test becomes conservative.
• Higher/lower CV than expected: We go up/down towards conservative levels.

Beeing on the ‘top of the ridge’ would mean IMHO that we are practically working with alpha_1,2 = 0.0294.

❝ BTW, empiric power is also interesting:

❝

❝

Another rather clear message of this nice picture: Don't use n1 as low as 12 ('internal pilot' in the usual understanding of many sponsors) if the anticipated CV is >25%.