“Group-by-Treatment Interaction” [Design Issues]
Hi GM,
Yep, the 1999 (!) infamous one. Groups separated by two weeks. See the FDA’ applicable guidance (2001), Section VII.A.
0.1 not 0.05. BTW, did you bother reading the presentation I linked in my OP?
Do you have a replicate design in mind? For ABE, no problem. For the EMA’s ABEL, doable. For the FDA’s RSABE, difficult. Ask three statisticians only to get get four options. Possible that the FDA insists on the fifth nobody has thought about. Difficult terrain.
Let’s assume that you plan the study in such a way that groups are not expected to differ (see ElMaestro’s post).
❝ I have seen one FDA BE review […].
Yep, the 1999 (!) infamous one. Groups separated by two weeks. See the FDA’ applicable guidance (2001), Section VII.A.
❝ Here agency is asking for the BE of any one of the group, if group-by-treatment interaction is significant (p<0.05).
0.1 not 0.05. BTW, did you bother reading the presentation I linked in my OP?
❝ Is it possible in studies conducted on HVD?
Do you have a replicate design in mind? For ABE, no problem. For the EMA’s ABEL, doable. For the FDA’s RSABE, difficult. Ask three statisticians only to get get four options. Possible that the FDA insists on the fifth nobody has thought about. Difficult terrain.
❝ Please provide your thoughts on the same.
Let’s assume that you plan the study in such a way that groups are not expected to differ (see ElMaestro’s post).
- FDA, Gulf Cooperation Council, Russian Federation, Eurasian Economic Union
Give a justification (in the protocol!) that all criteria will be met and go full throttle with the pooled analysis.
FDA: If in doubt, start a controlled correspondence.
The others: There are no scientific advices, only private dinners. Consider ‘Model II’.
- EMA
Thousand of studies accepted in multiple groups without problems (two exceptions in my presentation). If you prefer braces with suspenders, state ‘Model II’ in the protocol. Loss in power compared to the pooled analysis is negligible.
- If there is no true group-by-treatment interaction, in 10% of cases you will detect one by pure chance (false positive). No pooling, analysis of separate groups, power to show BE – even in the largest one – low.
- Any pre-test can inflate the Type I Error.
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Dif-tor heh smusma 🖖🏼 Довге життя Україна!
Helmut Schütz
The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes
Dif-tor heh smusma 🖖🏼 Довге життя Україна!
Helmut Schütz
The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes
Complete thread:
- Possible reasons for group effect GM 2019-07-20 07:36 [Design Issues]
- Group “effect” Helmut 2019-07-20 14:02
- Possible reasons for group effect ElMaestro 2019-07-20 19:20
- Possible reasons for group effect GM 2019-07-23 06:23
- “Group-by-Treatment Interaction”Helmut 2019-07-23 10:32
- Possible reasons for group effect GM 2019-07-23 06:23