[R-sig-ME] Large variance and SD for random effects

[cumuluss]

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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> 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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>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>
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