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

Kornbrot, Diana d@e@kornbrot @ending from hert@@@c@uk
Thu Nov 22 18:09:56 CET 2018

So I am comparing standard ANOVA on raw  frequencies (or equivalently probabilities) with GLMM for  binomial  proportion with both  logit and probit   link
ALL analyses have  been completed in SPSS using MIXED for: response   = identity ,  link = normal ; response =  proportion=freq/Nmax, link =  probit; response = proportion link  = logit)
I want   to show  how to  do identical  analyses in R using lmer  for are freq and  glmer for proportions
So I wasn’t SAME results  from R and SPSS (and a  diamond  necklace for Christmas,  celebrated as  an EU citizen in UK - I am a demanding woman)
Results are NOT quite  the same.
I am  checking using  the raw  probabilities as raw response with lmer before  moving  on to  glmer  for proportions
Check 1, in SPSS for raw  freq or  probability REPEATED  give  same  result   as  MIXED (response = identity, link = normal). where  there are differences it is REPEATED WITHIN  comparisons  not MULTIVARIATE.
Check 2. Compare R,  lmer with SPSS  mixed
if repeated groups are w1,  w2,  etc  and between groups are b1,  b2  etc, I use:
result <- lmer(freq~b1*b2*w1*w2 + (w1|subject)  + (w2|subject),  data  =  test)
Fand df from R  and SPSS do  not always match,  even  when  they do  match on sums  of squares
I am trying  to  work out WHY there is a mismatch
Thought that  knowing what was in the DENOMINATOR of the F values - which i perhaps  wrongly termed  error sums  of squares, might help

I  want F  for usual reasons:   to test significance  and estimate  effect  size.
I also want  all  my packages  to  give  me the SAME F and df2 and to  UNDERSTAND what is happening

Sorry this is  so long,  but  hope it is now clearer



and as  an extra  treat  would like marginal means from object  of type lmer

Dear Diana,
If indeed what you're looking for is what Rolf mentioned, you might find Nakagawa & Schielzeth (2013) helpful.
It's titled "A general and simple method for obtaining R2 from generalized linear mixed-effects models". There is no dispute about the method's generality, but simple is a relative term...
Here's the link: https://besjournals.onlinelibrary.wiley.com/doi/epdf/10.1111/j.2041-210x.2012.00261.x

Hope this helps,
Roi Maor
PhD candidate
School of Zoology, Tel Aviv University
Centre for Biodiversity and Environment Research, UCL

Professor Diana Kornbrot
+44 (0) 7403 18 16 12
University of Hertfordshire
College Lane, Hatfield, Hertfordshire AL10 9AB, UK
+44 (0) 170 728 4626
d.e.kornbrot using herts.ac.uk<mailto:d.e.kornbrot using herts.ac.uk>
skype:  kornbrotme
19 Elmhurst Avenue
London N2 0LT, UK
+44 (0) 208 444 2081

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