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Hello Zan,
As mentioned above, I do not think there is any formal guidance. If you have a reason to analyse a factor at 0.05 then do that. If you have a reason to analyse it at 0.1 then do that. I can't give you the optimal reason or the right alpha as it could come down to the specifics associated with your product/API. It all makes little sense to discuss alpha if you are not going to react to significance anyway. So this discussion is more than just the choice of alpha, it is also about what to do with tests that are significant.
Do what you think is right, fair, ethical and decent and what your SOP tells you to do.
At the end I think the principal distinction of BE versus not BE is made on basis of the confidence interval so the decision is not directly associated to the P-values of the ANOVA (that's unless you are a Danish regulator but we'll leave it out of this discussion for now).
Bear in mind that in the ANOVA you are testing hypothesis of equality.
This stands in contrast to the null hypothesis we evaluate when we test for bioequivalence.
Therefore, to me most anova p-values (regardless of alphas) are of secondary importance. If your randomisation was not effective (all the fat guys ended up in seq TR and all the slim ones in RT) then you might well see a sequence effect. If your first period was in the summer and the second period was in the winter then you might see a period effect. Etc. It will not necessarily have much to do with product performance.
❝ I am still wondering does FDA have any guidance regarding what significant level is recommended (0.05 or 0.1) for assessing all effects. What if I observe a period or sequence effect at 0.06.
As mentioned above, I do not think there is any formal guidance. If you have a reason to analyse a factor at 0.05 then do that. If you have a reason to analyse it at 0.1 then do that. I can't give you the optimal reason or the right alpha as it could come down to the specifics associated with your product/API. It all makes little sense to discuss alpha if you are not going to react to significance anyway. So this discussion is more than just the choice of alpha, it is also about what to do with tests that are significant.
Do what you think is right, fair, ethical and decent and what your SOP tells you to do.
At the end I think the principal distinction of BE versus not BE is made on basis of the confidence interval so the decision is not directly associated to the P-values of the ANOVA (that's unless you are a Danish regulator but we'll leave it out of this discussion for now).
Bear in mind that in the ANOVA you are testing hypothesis of equality.
This stands in contrast to the null hypothesis we evaluate when we test for bioequivalence.
Therefore, to me most anova p-values (regardless of alphas) are of secondary importance. If your randomisation was not effective (all the fat guys ended up in seq TR and all the slim ones in RT) then you might well see a sequence effect. If your first period was in the summer and the second period was in the winter then you might see a period effect. Etc. It will not necessarily have much to do with product performance.
—
Pass or fail!
ElMaestro
Pass or fail!
ElMaestro
Complete thread:
- Phoenix WNL to handle 2x2 crossover study with multip group zan 2014-06-27 23:29
![[Mix]](https://static.bebac.at/img/mix.png "open in Mix view")
- Phoenix WNL to handle 2x2 crossover study with multip group ElMaestro 2014-06-28 23:23
- Group effect commonly not relevant Helmut 2014-06-30 16:55
- Group effect in 2x2 BE study zan 2014-06-30 19:18
- Group effect in 2x2 BE study ElMaestro 2014-06-30 20:36
- To pool or not to pool Helmut 2014-06-30 20:51
- To pool or not to pool zan 2014-06-30 21:02
- To pool or not to pool Helmut 2014-06-30 21:38
- To pool or not to pool zan 2014-06-30 21:46
- To pool or not to pool Helmut 2014-06-30 22:22
- To pool or not to pool zan 2014-07-01 01:15
- Partial vs. sequential tests in WNL Helmut 2014-07-01 12:26
- Partial vs. sequential tests in WNL zan 2014-07-01 18:03
- Loosing patience Helmut 2014-07-01 18:23
- Partial vs. sequential tests in WNL zan 2014-07-01 18:03
- Partial vs. sequential tests in WNL Helmut 2014-07-01 12:26
- To pool or not to pool zan 2014-07-01 01:15
- To pool or not to pool Helmut 2014-06-30 22:22
- To pool or not to pool ElMaestro 2014-06-30 22:11
- To pool or not to pool zan 2014-07-01 01:18
- To pool or not to pool zan 2014-07-02 19:56
- To pool or not to poolElMaestro 2014-07-03 00:17
- To pool or not to pool zan 2014-07-03 00:36
- sequence- / period effect #666 Helmut 2014-07-03 10:05
- To pool or not to poolElMaestro 2014-07-03 00:17
- To pool or not to pool zan 2014-06-30 21:46
- To pool or not to pool Helmut 2014-06-30 21:38
- To pool or not to pool zan 2014-06-30 21:02
- Group effect commonly not relevant AngusMcLean 2014-07-06 16:19
- Group effect commonly not relevant Helmut 2014-07-06 20:32
- Group effect commonly not relevant AngusMcLean 2014-07-06 22:52
- Group effect commonly not relevant Helmut 2014-07-06 23:57
- PHX: Parameter mapping AngusMcLean 2014-07-07 15:04
- PHX: Parameter mapping Helmut 2014-07-07 15:45
- PHX: Parameter mapping Shuanghe 2014-07-07 17:35
- Great hint! Helmut 2014-07-07 17:54
- PHX: Parameter mapping AngusMcLean 2014-07-07 20:49
- PHX: Parameter mapping AngusMcLean 2014-07-07 18:46
- PHX: Parameter mapping Shuanghe 2014-07-07 17:35
- PHX: Parameter mapping Helmut 2014-07-07 15:45
- PHX: Parameter mapping AngusMcLean 2014-07-07 15:04
- Group effect commonly not relevant Helmut 2014-07-06 23:57
- Group effect commonly not relevant AngusMcLean 2014-07-06 22:52
- Group effect commonly not relevant Helmut 2014-07-06 20:32
- Group effect in 2x2 BE study zan 2014-06-30 19:18
Ing. Helmut Schütz