Bioequivalence and Bioavailability Forum

Hi Helmut,

❝ The negative final Variance Component warning most likely indicates that, if using Subj(Seq) as a random effect, the within-subject variance (residual) is greater than the between-subject variance. Probably a more appropriate model is to move Subj(Seq) out of the random model and into the fixed model, i.e.,

❝     Sequence+Subject(Sequence)+Formulation+Period

❝ ❝ Is it a convergence/optimizer thing?

❝

❝ Don’t think so. If you give me some days I will dig out a data set.*

Ah, now it is beginning to dawn on me what the heck is going on.
I am fairly certain this must be an optimizer problem associated only with a mixed effects model; some initial guesses are necessary to get started and of course the optimiser might sometimes pick something with higher between-s than within-s. Then everything could go south if the initial guess is too wrong. If I recall correctly the REML value has a vertical (yes oddly not not horizontal) attractor asymptote when the guesses are too wrong.
So I guess nothing to do with PROC GLM + "random" statement.

But then again why would anyone fit a 2,2,2-BE study with REML. It can be solved pseudo-exactly without an optimizer Al Gore Rhythm. And it involves all effects as fixed, even in the case of PROC GLM + "random".