[R-sig-ME] [FORGED] Error means squares in GLMER and LMER
r@turner @ending from @uckl@nd@@c@nz
Thu Nov 22 11:58:48 CET 2018
On 11/22/18 8:37 PM, Kornbrot, Diana wrote:
> My, supposedly helpfu,l predictive text programme has a warped sense of
> Unlike the R documentation which is tedious, verbose, is always sending
> me on wild goose changes and never seems to tell me what i need to know.
> Please, please
> How do I get those means square error terms form lmer and glmer?
I think your accusations against the R documentation are unfair.
Be that as it were, let me respond a little bit to your substantive
question. I am no expert, so take everything I say with a grain of
salt. Perhaps someone from the R-sig-ME list, who is more knowledgeable
than I, will give you better advice.
My conjecture is that you are having trouble getting hold of mean
squared error terms because there *aren't* any. Mixed models are not
based on sums of squares; they are *likelihood* based. Inference is
based on likelihood ratio tests, not on F-tests. The covariance matrix
for the coefficient estimates is formed as the inverse of the Fisher
Information matrix. It does not have the simple form that it has in the
context of ("un-mixed"; ordinary garden-variety) linear models.
Consequently you will need to readjust your thinking. The learning
curve for mixed models is steep. I have barely got my own toes onto the
bottom of the lowermost slopes.
I hope that I haven't misunderstood either your question or the
underlying structure of mixed models.
Technical Editor ANZJS
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276
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