Bioequivalence and Bioavailability Forum

Hi Helmut,

❝ For sure my confusion is caused by my peanut-sized brain. The GL states

The statistical analysis should take into account sources of variation that can be reasonably [sic] assumed to have an effect on the response variable.

Oh yes, but a fixed effect does not add to the (residual) variation or to the T/R.

❝ Think about my example (forget about Xovers now; see also this one). Even in large centers we might have more than one group per treatment due to difficult recruitment. What if one group shows only ⅛ of the ‘normal’ response? We know that handling and storage of samples in University hospitals might not be that well-controlled like in spezialised CROs… Can/should we pool the data in such a case? Not only the CV will be inflated, the treatment effect will be biased as well. Referring to the – canceled – presentation above it seems to me that the BfArM is concerned about “group and centre effects”.

Yes to pooling. This example would translate into a center effect (possibly center*group if you include such stuff in your muddle). At the end of the day you are interested in just the plain T and R estimates given the effect estimates from other terms in the muddle. I would consider the center effect a nuisance issue just like old-fashioned period effects. And bear in mind that center often comes out extremely significant even for innovator drugs.
The example serves well to illustrate a situation where the WS approach would spell trouble, even if the ideas of unequal variances is appealing. No way to decompose a variability into several factors however obvious they are, as far as I can tell.

❝

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P.S.: Any idea why I get unequal variances of T and R in ~28% of studies? I expect only ~5%…

No. Sorry I have not really tried to understand your code. Will do a transatlantic flight in a few days, perhaps it would be a way to kill time?