[R-sig-ME] Random vs. fixed effects
Daniel Ezra Johnson
danielezrajohnson at gmail.com
Fri Apr 23 15:47:41 CEST 2010
I'm not personally an expert, but from reading this list for some
time, the consensus is that three points is not enough to make a
reasonable estimate of a variance. Nor is a three-level effect likely
to be nested within a fixed effect, which would require it be treated
So yes, a fixed effect sounds like the way to go here, but as far as
what differences you'd get by treating it as fixed or random, in terms
of inference or prediction (from the BLUPs, if random) you might want
to investigate that. If you want to make predictions to new population
members, then of course random is your only choice.
On Fri, Apr 23, 2010 at 9:38 AM, Schultz, Mark R. <Mark.Schultz2 at va.gov> wrote:
> I just read a post by Andrew Dolman suggesting that a factor with only 3
> levels should be treated as a fixed effect. This seems to be a perennial
> question with mixed models. I'd really like to hear opinions from
> several experts as to whether there is a consensus on the topic. It
> really makes me uncomfortable that such an important modeling decision
> is made with an "ad hoc" heuristic.
> Mark Schultz, Ph.D.
> Bedford VA Hospital
> Bedford, Ma.
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