[R-sig-ME] [FORGED] Error means squares in GLMER and LMER

Rolf Turner 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 
> humour.
> 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

More information about the R-sig-mixed-models mailing list