[R-sig-ME] R2admb-package

[Ben Bolker]

  [cc'ing to r-sig-mixed-models]

  Yes, sort of: see the caveats listed at
http://glmm.wikidot.com/faq#random-sig, in particular the last one (the
LRT is conservative for tests of null hypotheses where the parameter is
at the boundary). anova(m1,m2) should give you a likelihood ratio test
for the difference.

  glmmADMB uses the Laplace approximation to maximum likelihood estimation.

On 14-07-14 05:16 AM, Elena Guerrero wrote:
> Dear Ben,
> 
> Is it possible to compare a glmmADMB model with a random term and and
> the same model without that random term, with an ANOVA, in order to know
> if the random term is significantly important? Does glmmADMB package use
> ML method? I have seen (http://glmm.wikidot.com/pkg-comparison) that it
> uses the Laplace estimation method, it is possible to make such
> comparison with this method?
> 
> My model is of the following type:
> Mugg_glmmADMB<-glmmadmb(Mugg ~ S10 + T10 + F10 + Prof+ offset (L.vol) +
> (1|Est), link = "log",
>                      data =tabla10m, zeroInflation=FALSE, family="nbinom")
> 
> Thank you very much in advance.
> Best regards,
> Elena


> 
> --
> Elena Guerrero Sánchez-Guerrero
> PhD student
> Dept. Biologia Marina i Oceanografia
> INSTITUTO DE CIENCIAS DEL MAR - CSIC
> Pg. Marítim de la Barceloneta, 37-49
> 08003 BARCELONA
> Spain
> Phone:(+34) 93 230 95 00 (ext. 1209)
> Fax: (+34) 93 230 95 55 
> http://www.icm.csic.es/icmdivulga/es/mediterraneo-monograficos-08.htm
> http://www.icm.csic.es/bio/
> 
> El 04/07/14 17:18, Elena Guerrero escribió:
>> Great, thank you very much Ben. I've got it!
>>
>> All the best,
>> Elena
>> --
>> Elena Guerrero Sánchez-Guerrero
>> PhD student
>> Dept. Biologia Marina i Oceanografia
>> INSTITUTO DE CIENCIAS DEL MAR - CSIC
>> Pg. Marítim de la Barceloneta, 37-49
>> 08003 BARCELONA
>> Spain
>> Phone:(+34) 93 230 95 00 (ext. 1209)
>> Fax: (+34) 93 230 95 55 
>> http://www.icm.csic.es/icmdivulga/es/mediterraneo-monograficos-08.htm
>> http://www.icm.csic.es/bio/
>> El 03/07/14 00:42, Ben Bolker escribió:
>>> -2*logLik() is the deviance, so you should be able to fill that into
>>> the formula.  To get the null deviance you will need something like
>>> null.model <- update(full.model, [formula including only an intercept
>>> term in the fixed effects]).  It is up to you to decide what a
>>> 'sensible' null model is -- i.e. whether it includes the random
>>> effects or not ...
>>>
>>>
>>> On Wed, Jul 2, 2014 at 9:23 AM, Elena Guerrero <eguerrero at icm.csic.es
>>> <mailto:eguerrero at icm.csic.es>> wrote:
>>>
>>>     Dear Ben,
>>>
>>>     Thank you very much for your fast reply.
>>>
>>>     I've tried: "-2*logLik(My glmmADMB)" and it gave me: 'log Lik.'
>>>     1854.08 (df=7).
>>>
>>>     How should I interpret this result? Is is possible to obtain a
>>>     proportion % value of the explained deviance by the model?
>>>
>>>     Thank you very much!
>>>     All the best,
>>>     Elena
>>>
>>>
>>>     --
>>>     Elena Guerrero Sánchez-Guerrero
>>>     PhD student
>>>     Dept. Biologia Marina i Oceanografia
>>>     INSTITUTO DE CIENCIAS DEL MAR - CSIC
>>>     Pg. Marítim de la Barceloneta, 37-49
>>>     08003 BARCELONA
>>>     Spain
>>>     Phone:(+34) 93 230 95 00 <tel:%28%2B34%29%2093%20230%2095%2000>
>>>     (ext. 1209)
>>>     Fax: (+34) 93 230 95 55 <tel:%28%2B34%29%2093%20230%2095%2055>
>>>     http://www.icm.csic.es/icmdivulga/es/mediterraneo-monograficos-08.htm
>>>     http://www.icm.csic.es/bio/
>>>
>>>     El 01/07/14 23:03, Ben Bolker escribió:
>>>
>>>           [cc'ing to R-sig-mixed-models]
>>>
>>>            There appears to be a deviance() method for 'admb' objects
>>>         (produced
>>>         by R2ADMB), but not for 'glmmadmb" objects (produced by
>>>         glmmADMB).
>>>         However, you should be able to use -2*logLik(object) to
>>>         obtain the
>>>         deviance (to be precise, -2*logLik(object) is equal to the
>>>         deviance in
>>>         general only _up to an additive constant_, but I think this
>>>         workaround
>>>         will be OK for your purposes).
>>>
>>>            Ben Bolker
>>>
>>>
>>>         On 14-07-01 07:10 AM, Elena Guerrero wrote:
>>>
>>>             Dear Ben Bolker,
>>>
>>>             I have run a glmmADMB model to my count data with a
>>>             family = "nbinom" .
>>>             It worked very nice.
>>>
>>>             Now I want to calculate the *deviance explained* by this
>>>             model
>>>             (100*(Null deviance-Residual deviance)/Null deviance). I
>>>             installed the
>>>             R2admb package to use the deviance() function, however
>>>             when I write
>>>             deviance(my model) R gives me "NULL" as a response. When
>>>             I try with the
>>>             "admbex" example it works perfectly.
>>>
>>>             What is it happening? What does mean NULL in this case?
>>>             Is there any
>>>             other way to obtain the explained deviance of a glmmADMB
>>>             model?
>>>
>>>             Thank you very much in advance.
>>>             Best regards,
>>>             Elena
>>>
>>>             -- 
>>>             --
>>>             Elena Guerrero Sánchez-Guerrero
>>>             PhD student
>>>             Dept. Biologia Marina i Oceanografia
>>>             INSTITUTO DE CIENCIAS DEL MAR - CSIC
>>>             Pg. Marítim de la Barceloneta, 37-49
>>>             08003 BARCELONA
>>>             Spain
>>>             Phone:(+34) 93 230 95 00
>>>             <tel:%28%2B34%29%2093%20230%2095%2000> (ext. 1209)
>>>             Fax: (+34) 93 230 95 55
>>>             <tel:%28%2B34%29%2093%20230%2095%2055>
>>>             http://www.icm.csic.es/icmdivulga/es/mediterraneo-monograficos-08.htm
>>>             http://www.icm.csic.es/bio/
>>>
>>>
>>>
>>
>