Group effect commonly not relevant [Software]

posted by Helmut Homepage – Vienna, Austria, 2014-06-30 18:55 (3948 d 13:35 ago) – Posting: # 13174
Views: 27,758

Hi Zan,

first I agree with what ElMaestro wrote. Two groups are no issue generally (same protocol, same site, not too large interval [months!] between groups).
Maybe you are interested in this thread and some quotes from the FDA. I don’t have Win­Nonlin any more (consider upgrading to Phoenix; release 6.4 is expected this summer). My setup in Phoenix / Win­Nonlin 6.3:
Like any between-subject test the one for Treatment-by-Group is lacking power (therefore, testing at α 0.10). However, you could expect then a false-positive rate in 10% of studies!

❝ I am working on a 2x2 crossover BE study with large N (N=54). Due to limited clinical capacity the site separated subjects into two dosing groups (N=27 each).


IMHO, a 1:1 split is not optimal. Let’s assume the worst, i.e., for any wacky reasons FDA insist on model I and there is a significant Treatment-by-Group Interaction. No pooling; go with one of the groups. In your design both have a size of 27. Let’s assume a T/R of 0.95, CV 30.5%, and target power 90%. You end up with 54 subjects (power 90.38%). BTW, your 1:1 split results in imbalanced sequences in both groups. Let’s further assume that in both groups the T/R-ratio and CV come out exactly as planned and you have no drop-outs. Power will be just 60.97% in both. If both groups are equally sized the questions also arises on which one you will base the assessment of BE. The nicer one? :cherry picking:
I would suggest to split subjects in such a way that one of the groups is the maximum capacity of the clinical site. Which power can we expect in the groups?
G1  % power  G2  % power
────────────────────────
27   60.97   27   60.97 
28   63.13   26   58.63 
30   66.92   24   53.92
32   70.27   22   48.33 
34   73.25   20   41.98 
36   75.89   18   34.91 
────────────────────────

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