## Hey, hey wait another moment.... [General Sta­tis­tics]

Dear Detlew,

» IMHO we don't need an alpha correction for your case above, if we combine the tests with 'and'.

THX for reminding me (not for the first time)…

» Seems a case for sims if we don't trust in the Reference. Isn't it?

In God we trust;
all others must bring data.
W. Edwards Deming

» Eventually we can miss-use power.2TOST() if we consider for simplicity two simultaneous test of AUC_T1R and AUC_T2R as the two metrics, which are usually interpreted as two different metrics, e.g. AUC and Cmax, respectively.
» Then of course the question of the correlation parameter rho arises. How to choose?

Not sure. Whereas two PK metrics are always correlated somehow, IMHO, here it may be different. One formulation doesn’t care how it behaves in relation to the other. Too lazy to browse through my pilot studies. I’m pretty confident that some kind of correlation will show up but I doubt that it will be causation. PK is relatively simple but the outcome of a PK study with different formulations depends on an awful lot of manufacturing / process parameters. I think that the safe way would be subjects simulations. Normally for the TIE we use a true GMR of one of the BE-limits and add variability. How to do that in a higher order design? Say for one subject I will have R=1, T1=1.25±se, T2=1.25±se.
Now what?

Dif-tor heh smusma 🖖
Helmut Schütz

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