[R-sig-ME] Large variance and SD for random effects
cumuluss
cumuluss at gmx.de
Tue Mar 6 17:56:00 CET 2018
Dear Thierry,
thank you for your answer and especially for the quotation.
I will follow your suggestion.
Best regards
Paul
Thierry Onkelinx:
> Dear Paul,
>
> Yes, I see no point in keeping an unstable model. Remember "All models are
> wrong but some are useful" (Box, 1979). I'd investigate where the complete
> separation occurs and decide which random slope should be removed.
>
> In case of the strong correlations among random effects see
> https://www.muscardinus.be/2018/02/highly-correlated-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
>
> ///////////////////////////////////////////////////////////////////////////////////////////
> 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
> The combination of some data and an aching desire for an answer does not
> ensure that a reasonable answer can be extracted from a given body of data.
> ~ John Tukey
> ///////////////////////////////////////////////////////////////////////////////////////////
>
> <https://www.inbo.be>
>
> 2018-03-06 11:02 GMT+01:00 cumuluss <cumuluss at gmx.de>:
>
>> 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
>>>
>>> ////////////////////////////////////////////////////////////
>> ///////////////////////////////
>>> 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
>>> The combination of some data and an aching desire for an answer does not
>>> ensure that a reasonable answer can be extracted from a given body of
>> data.
>>> ~ John Tukey
>>> ////////////////////////////////////////////////////////////
>> ///////////////////////////////
>>>
>>> <https://www.inbo.be>
>>>
>>> 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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>>>>
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