Lost on the Bear way [RSABE / ABEL]

posted by d_labes  – Berlin, Germany, 2010-03-30 11:20 (5140 d 11:02 ago) – Posting: # 4992
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Gents!

❝ ... Schützomycin is an esoteric (aka undocumented) ingredient of modern preparations of Flying Ointment. You don’t smoke it, honey – its use is topical & delicate; believe me. :cool:


Ok, on my next leg along the Bear way I will take some dose of Schützomycin with me. Hopefully this will escape me from some more serious situations.

❝ ... Rumors are going that he’s on the track of evaluating a replicate study without a mixed model and all effects fixed. :lookaround:


Yessss Sir, this is the Bear way, without lme() but rather lm() also known to SAS'lers as Proc GLM :yes:.

And what I have observed in this adventure along the Bear way was to evaluate my original question Q2 above in this thread: How can we get the 'appropriate' tests (new BE guidance, page 16 "The ANOVA tables, including the appropriate statistical tests of all effects in the model, should be submitted.") within an ANOVA style evaluation.

And I was very surprised with that finding as a statistical raw recruit.

If it is real, and the right answer to a false question, it prevents us from using a test by hand of the sequence effect using simply the subject(sequence) MS as the error term because the mixture observed above depends on the degree of imbalance.
Just to cite ElMaestro above, ooouch ..., below: "You still can get the effects right ... by considering all effects fixed. but you will have to do some manual brain-work still."
I employed the RANDOM statement to save my small brain.

I suppose a big amount of serious headache! For every new study, if using 3-period-whatever-sequence replicate design, if not totally balanced! Schützomycin to the rescue? :lookaround:

BTW: In a bizarre twist, it's not all-fixed but rather mixed as usual, but ANOVA, ANOVA, ANOVA ...
BTW2: The Bear model is also used in Chow/Liu, Chapter 9 but evaluated with GLM (see for instance page 274). Also the various formula given there (casually also for the within-subject variabilities!) then heavily rely on within-subject contrasts.

Regards,

Detlew

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