Bioequivalence and Bioavailability Forum

Howdy ElMaestro!

❝ I can learn a lot, and there is a loooooong way to go for me.

For all of us…

❝ I wonder about a issue that is on the border between philosophy and statistics... Analysis of Log C_max is generally based on the assumption that the residuals are normal.

Yep.

❝ If we subsequently also want to qualify Log C_min with some kind of statistic can we then conduct such an analysis with parametric statistics? Once we identify Log C_max we know that the rest will be smaller than that value.

We also know, that the residuals of AUC will always be lower than the ones of C_max.

❝ Hence, there are constraints on the magnitudes of the residuals in the analysis of Log C_min and therefore I would be inclined to think we violate an important assumption in parametric statistics?

Not quite. The assumptions in the parametric model of any given metric are independent from each other,
Untransformed metrics have limits of [-∞, +∞], whilst log-transformed have limits of [>0, +∞], but in both cases the probability equals 1 (in other words, for C_min and C_max the log-transformation lead to the same lower limit – I wouldn’t call it a constraint – namely zero).

❝ (I shall abstain from proposing parametric statistics as a potential alternative, notch notch wink wink!)

You mean nonparametric statistics? Well, cough…