Replicated designs are relevant, too [Software]

posted by ElMaestro  – Denmark, 2014-10-07 14:36 (3865 d 05:15 ago) – Posting: # 13663
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Hello yjlee,

❝ Why jump into '2-group parallel'? What about replicate?


2-group parallel are probably still the second-most common BE design, I think, and that's to me quite a good argument for prioritising it.

As you say, replicate designs are also relevant, but it would open up a can of worms:
  1. EU all fixed effects (=normal linear model) versus US subject as random (=mixed model) and the EU vs US way of scaling.
  2. Various modes of imbalance (missing period data or different numbers in TRTR and RTRT etc)
  3. The use of denominator degrees of freedom as per Satterthwaite or something else; software limitations on the same matter.
Finally, I think noone that I know of doing BE is 100% well versed with the inner workings of mixed models or the syntactical wonders and settings of R, SAS, Nonlin, SPSS or whatever which to some extent would need deep understanding if we go the US route. With mixed models there will be quite a few potential choices to make and this is when the understanding matters a lot. For starters: Do we use REML and not ML because we have a read some webpages or books suggesting REML and not ML, or do we use REML because we have a deep understanding of the merits of REML and the lack of same for ML in the context of BE? Syntax for fits are complex regardless of language/package and how exp units are coded, e.g. "fm3 <- lmer(strength ~ (1|batch) + (1|batch:cask), Pastes)" and who really knows what all that "~" and "|" does for your ZGZt+R? If you use an option to do Kenward-Rogers are you then not compliant? And then there are the optimiser settings. And so forth.
Tricky, tricky, tricky.

Pass or fail!
ElMaestro

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