Desultory thoughts [🇷 for BE/BA]

posted by ElMaestro  – Denmark, 2020-07-16 01:06 (1799 d 23:49 ago) – Posting: # 21705
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Hi Hötzi,

❝ ❝ to me it is exactly the opposite way around:

❝ ❝ A model with more than one variance component is a mixed model.

❝

❝ Not necessarily. It depends on what you believe [sic] is a random effect. Treatment, sequence, and period are fixed effects, right? IMHO, subject is random. When we think about interaction(s) we enter the gray zone, of course.


May I offer the completely opposite view? Search the forum for "bogus statement" :-D, check the SAS documentation for what the statement actually actually does to Proc GLM:
When ProcGLM is used for 222BE with or without the bogus statement it still means a normal linear model is fit (even when the theory in e.g. C&L calls it "random"). There is a single variance component in such fits. If you wish to verify it: There is a model matrix with columns for subjects; check the df's for such models, it would be (much) higher if subjects were fit as random. Conversely, if subject were random subject would not appear as a factor in the anova.
—
Pass or fail!
ElMaestro

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