Large variance and SD for random effects

Dear Thierry,
sorry one more question. i would like to ask whether you could give me
some recommendation for my model. Would you skip random effects (or
slopes) even if you think they are necessary, as far as they lead to
suffering models? It is maybe a more general question.
Thank you!




Dear Thierry,
thank you for your answer!
Ok then I have to rethink the model.
Best regards
Paul



Thierry Onkelinx:

Dear Paul,

Your random effect structure looks quite complicated. Maybe too complex

for

the data. Your model is very likely suffering from (quasi) complete
separation.

Besides the large variances, you should also be alarmed by the near

perfect

correlations among some random effects.

Best regards,



ir. Thierry Onkelinx
Statisticus / Statistician

Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE

AND

FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry.onkelinx at inbo.be
Havenlaan 88 bus 73, 1000 Brussel
www.inbo.be

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To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to

say

what the experiment died of. ~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data. ~ Roger Brinner
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ensure that a reasonable answer can be extracted from a given body of

data.

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2018-03-05 20:24 GMT+01:00 cumuluss <cumuluss at gmx.de>:

Hello,
the result of my GLMM with binomial error structure revealed for one of
the random intercepts and slopes variances and Sd's larger then 1

Generalized linear mixed model fit by maximum likelihood (Laplace

Approximation) ['glmerMod']

 Family: binomial  ( logit )
Formula: obs.yn ~ z.lengthxyz + z.obsX + Spe_tr_subspecie + (1 |

commu) +

    (1 + z.lengthxyz + z.obsX | Siteun) + (1 + z.lengthxyz +
    z.obsX + Spe_tr_subspecie_a.c + Spe_tr_subspecie_b.c +
    Spe_tr_subspecie_c.c | behavior)

Random effects:
 Groups   Name                  Variance Std.Dev. Corr
 commu    (Intercept)           0.614004 0.78358
 Siteun   (Intercept)           0.521198 0.72194
          z.lengthxyz           0.001016 0.03188   1.00
          z.obsX                0.306931 0.55401  -0.17 -0.19
 behavior (Intercept)           2.966139 1.72225
          z.lengthxyz           0.030171 0.17370   0.77
          z.obsX                0.412169 0.64200   0.20 -0.36
          Spe_tr_subspecie_a.c  1.853903 1.36158   0.58  0.62  0.11
          Spe_tr_subspecie_b.c  3.973439 1.99335   0.51  0.23  0.25

0.65

          Spe_tr_subspecie_c.c  7.401343 2.72054   0.39  0.30  0.47

0.79  0.60

Number of obs: 4413, groups:  commu, 144; Siteun, 108; behavior, 31

Now I wonder, whether that is a reason to worry, that the result could
be not valid?
Thanks in advance for any comments!
Paul

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