GMR, theta0 and that all [Two-Stage / GS Designs]

posted by d_labes  – Berlin, Germany, 2017-03-09 13:55 (1410 d 05:46 ago) – Posting: # 17147
Views: 10,373

Dear Silva,

additionally to what our great Maestro said:

You have to know beforehand if your settings you use in a TSD i.e. adj. alpha, fixed GMR, targetpower, n1, inclusion of futility rules or other are suszeptible to an alpha-inflation over a range of reasonable true CV.
Potvin have that shown for adj. alpha = 0.0294, targetpower 0.8 and n1 12-60 for a range of true CVs of 10-100% by simulations, at least for the Type 1 (aka method B) decision scheme. For Type 2 (aka method C) decision scheme some guys believe they have seen an alpha-inflation in the numbers given.

Anders the Great has derived adj. alpha values for other settings of the fixed GMR and targetpower preserving also the maximum TIE <=0.05.
  1. Fuglsang A. Controlling type I errors for two-stage bioequivalence study designs. Clin Res Regul Aff. 2011;28(4):100–5. doi 10.3109/10601333.2011.631547
  2. Fuglsang A. Sequential Bioequivalence Trial Designs with Increased Power and Controlled Type I Error Rates. AAPS J. 2013;15(3):659–61. doi 10.1208/s12248-013-9475-5
If you change any of these settings you have to show again that no alpha-inflation is to be expected. By simulations (... although there is some rumor that some leading regulatory agencies don't like simulations).
And that is to what end package Power2Stage was invented.

The observed GMR(s) and CV in your actual study don't play a role in that game. Not known beforehand ;-).
One exception: If you observe a CV > the 'validated' range it may be wise to do simulations with that CV assumed as TRUE.



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