Bioequivalence and Bioavailability Forum

Dear D. Labes!

❝ But which model ever, we make the assumption that the replicates are not the (random) result of the same formulation given at two occasions to the same subject, but something different. And that is to me not justifiable. Which effects should induce such a behaviour that we could separate the effects of the replicates?

Well, that's a similar kind of folk dance like EMA's arbitrary discarding test administrations from the model (Q&A, Section 3.4). Let's read it again:

An advantage of Method C is that it directly calculates s²_wr. However, sometimes the algorithm fails to converge. For that reason the preferred way to get an unbiased estimate of sigma²_wr is using the data from the reference product only.

The following code removes all the test data from the data-set and then fits a model where the residual variance corresponds to the within subject variance for the test product.

Bonus questions:

1. Is the crippled model only preferred by EMA because Model C may not converge in all cases?
   
2. Is it acceptable to calculate s²_wr by Method C and only retreat to EMA's model if convergence is not reached (preferred # mandatory)?
   
3. Of course the evaluation for BE has to be done by Methods A or B ("compatible with CHMP guideline"). Can we perform the scaling based on s²_wr from the "advantageous" [sic!] Method C?
   
4. The last sentence is funny: within subject variance for the test product.

❝ To me a point estimate R2/R1 different from =1 does not make sense therefore.

OK, wrong model, but possible due to chance.