[R-sig-ME] Error means squares in GLMER and LMER
bbolker @ending from gm@il@com
Thu Nov 22 20:44:27 CET 2018
For marginal means, use the emmeans package.
If you use the lmerTest package, you can get Satterthwaite or
Kenward-Roger df: you can use lme (from the nlme package), or
to get df via a simple "parameter-counting" exercise.
The problem is that the "F statistics" are quite poorly defined for
GLMMs. Can you show us the contrasting results you're getting for SPSS
and glmer? Do you know how SPSS is computing the F statistics? (This
makes it seem like it might be using Satterthwaite approximations ...)
On Thu, Nov 22, 2018 at 12:09 PM Kornbrot, Diana
<d.e.kornbrot using herts.ac.uk> wrote:
> 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
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