Study conduct in groups [Design Issues]

posted by ElMaestro  – Denmark, 2015-02-05 00:58 (3339 d 09:45 ago) – Posting: # 14373
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Hi Felipe,

❝ Once I have questioned the same inclusion of group effect analysis and the biostat said that this effect could appear when you cannot give the treatments to whole sample size at the same time/day. (statement 1)


Probably a misunderstanding. The biostatistician was prolly thinking loud: The need for dosing in groups arise when you cannot dose all subjects in the same time/day.

❝ However group effect is not a big deal such as sequence, treatment or period effect. (statement 2)


Those are not considered big deals either, but it also comes down to who's judging your dossier.
In (average) BE you test the null hypothesis:
Test differs from Ref.

In contrast, when you look at an ANOVA with all its impressive P-values they are test of other null hypotheses:
Test equals Ref.
Sequence TR equal Sequence RT.
Period 1 equals Period 2.
Subjects 1 equals Subject 2 equals .... subject N.
Group 1 equals Group 2.

All these tests are interesting and look like advanced science. They don't deal so much with the important issue at hand.
The real BE null hypothesis just requires the two treatment effects as the residual variance. All these three come from the model fit, not from the anova, although you'll often see it explained wrongly in certain books or guidelines. Simply stated you do (well, should) not really need an ANOVA to judge bioequivalence.

Note an important pitfall related to the above: When you look at an ANOVA with a significant treatment effect, then you are rejecting the null hypothesis Test equals Ref, but this doesn't say anything definitive about your acceptance or rejection of the null hypothesis: Test differs from Ref.
The reason is the equivalence margin.

Finally, group is a between-factor. It does not affect the residual variance if the model is specified correctly.

I hope this helps.

Pass or fail!
ElMaestro

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