It is the opposite way around for me [R for BE/BA]

posted by ElMaestro  – Belgium?, 2020-07-15 14:25 (30 d 12:20 ago) – Posting: # 21701
Views: 4,475

Hi again,

to me it is exactly the opposite way around:
A model with more than one variance component is a mixed model. I am of the impression that FDA and EMA have both been in a slight predicament with their guidances because they have both been "somewhat" aware of the specification/convergence issues with REML; hence both went in a direction with all effect s fixed as done explicitly by EMA and implicitly by FDA (when they use GLM for swr) in the guidance.
My contribution here is solely to open someone's eyes to the fact that we may not need to rely on a normal linear model for s2wr in a TRR/RTR/RRT design.

I would much more like to think of this thread as a contribution to regulators defining the next iteration of giudelines/guidances. Whether they will see it as an advantage to use REML to derive s2wr now it is shown to be doable (not causing convergence issues, because it is not involving the silly and unestimable s2wt component), is of course their decision solely. I have done my part.

For consideration further down the line, for those who enter discussions about estimator bias being catastrophic: Which estimator is more biased when handling RRT/RTR/TRR: the s2wr you get from the linear model or the one you get via REML? What would your answer imply for any future recommendations for guidelines/guidances?
(I am not a hardliner myself: I am usually thinking biased estimators are still useful estimators)

This thread already caught the attention of a number cruncher at an agency across the Atlantic unofficially, so I am OK with it all:-)

I could be wrong, but...

Best regards,
ElMaestro

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

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