## took just 52 hrs to do it :-) [R for BE/BA]

Hi Hötzi,

I think expressing the G matrix after this fit is a little backward;
The whole point is not to decompose V into ZGZt+R, because this design makes that decomposition pointless even when the design is otherwise relevant.
That SAS and WinNonlin and more do not have a way to make provisions for a solution outside those involving this decomposition, it merely a testament to their development capabilities than to the design itself. If you start defining the the stats model on basis of G and R rather than V then obviously you must create two variance components which are not uniquely estimable, but whose sum is. Therefore, just screw R and G, go directly for V, and present the components without in any way calling them members of G or R - they really aren't when the model is constructed my way.

The 2-trt, 3-seq, 3-per design is good, healthy and appropriate, until now it was just the statistical work on it that has been lagging. The post is an attempt at providing a solution.

Note also: The PE will be accessible via the est.b vector. You shuld be able to extract it (difference between first two effects, one good reason to do X without intercept) after the model has converged.

If you have a dataset that does not readily converge with SAS then I'd be eager to learn if it does in some flavour of my code.

I could be wrong, but...

Best regards,
ElMaestro

"Pass or fail" (D. Potvin et al., 2008)