Grazie Achaz,
the tutorial you linked gives useful hints.
I will consider the bayesian route but at the moment I am looking for a
reference that legitimates me to keep the poisson error distribution with
glmer and catch the overdispersion in the few models where my actual random
effects looks like not performing good enough.

Since I read that quasipoisson and quasibinomial distribution of errors are
not reliable in lme4 package and I would like not to rerun analysis with a
new package for this time, if possible!

Actually the observation level random effect works fine for my purpose.

Ciao

Enrico


2013/11/26 Achaz Hardenberg <achaz.hardenberg@gmail.com>

>
> Achaz von Hardenberg,
>
> --------------------------------------------------------------------------------------------------------
> Centro Studi Fauna Alpina - Alpine Wildlife Research Centre
> Servizio Sanitario e della Ricerca Scientifica
> Parco Nazionale Gran Paradiso, Degioz, 11, 11010-Valsavarenche (Ao), Italy
>
> E-mail: achaz.hardenberg@pngp.it
>      fauna@pngp.it
> Skype: achazhardenberg
> Twitter: @achazhardenberg
>
> Course on Phylogenetic comparative methods and Path Analysis:
> http://www.transmittingscience.org/pcm.htm
>
> PNGP Ricerca e Conservazione:
> http://www.pngp.it/natura-e-ricerca/conservazione-e-ricerca/ricerca
> LIFE+ BIOAQUAE Project: http://www.bioaquae.eu<http://www.pngp.it/natura-e-ricerca/conservazione-e-ricerca/ricerca>
> ResearchGate: https://www.researchgate.net/profile/Achaz_Von_Hardenberg/
> Google Scholar Citations: http://goo.gl/n0rYZ
>
> --------------------------------------------------------------------------------------------------------
>
>
>
> Hi Enrico,
> I would suggest you send this question to the R mixed models group
> (R-sig-mixed-models).
> However, to deal with over dispersion, I would go the Bayesian route,
> using mcmcGLMM which by default deals with over dispersed data.
> See the following reply by the developer of mcmcGLMM, Jarrod Hadfield to a
> similar question like yours:
> http://markmail.org/message/7rebq2tkbgfniwma
>
> The following tutorial by Ben Bolker may be useful as well
> http://glmm.wdfiles.com/local--files/examples/overdispersion.pdf
>
> Hope this helps!
> ciao,
> Achaz
>
>
> Achaz von Hardenberg,
>
> --------------------------------------------------------------------------------------------------------
> Centro Studi Fauna Alpina - Alpine Wildlife Research Centre
> Servizio Sanitario e della Ricerca Scientifica
> Parco Nazionale Gran Paradiso, Degioz, 11, 11010-Valsavarenche (Ao), Italy
>
> E-mail: achaz.hardenberg@pngp.it
>      fauna@pngp.it
> Skype: achazhardenberg
> Twitter: @achazhardenberg
>
> Course on Phylogenetic comparative methods and Path Analysis:
> http://www.transmittingscience.org/pcm.htm
>
> PNGP Ricerca e Conservazione:
> http://www.pngp.it/natura-e-ricerca/conservazione-e-ricerca/ricerca
> LIFE+ BIOAQUAE Project: http://www.bioaquae.eu<http://www.pngp.it/natura-e-ricerca/conservazione-e-ricerca/ricerca>
> ResearchGate: https://www.researchgate.net/profile/Achaz_Von_Hardenberg/
> Google Scholar Citations: http://goo.gl/n0rYZ
>
> --------------------------------------------------------------------------------------------------------
>
>
>
>
>
>
>
>
>
> On 26 Nov 2013, at 11:00, Enrico Caprio <enrico.caprio@gmail.com> wrote:
>
> Dear R-ecologists,
> I am running several mixed models (using glmer function of lme4 library) of
> count data (species richness and abundances).
> My data are spiders and ground beetles trapped in pitfalls in different
> locations and habitats and in different periods during a season.
>
> The best approach to analyze them for me was building a mixed model, using
> the pitfall in each location, the locations and the periods as random
> factor.  Habitat type and habitat variables are fixed factors.
>
> This approach deals well with overdispersion in most of the models, but in
> few cases I still have overdispersion. I read in forums and learned at some
> stat courses that a way to deal with overdispersion is using the
> observation level as  an extra random factor and this works fine but I
> would like to read something more about this and need some references.
>
> Do you know a paper or book that can help me with that?
>
> Thanks!
>
> Enrico
>
> --
> Enrico CAPRIO, PhD
> Laboratorio di Ecologia Animale
> Dipartimento di Scienze della Vita e Biologia dei Sistemi
> Via Accademia Albertina, 13
> I - 10123 Torino
> Cell. 3332134420
> http://www.personalweb.unito.it/enrico.caprio/
>
> [[alternative HTML version deleted]]
>
> _______________________________________________
> R-sig-ecology mailing list
> R-sig-ecology@r-project.org
> https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
>
>
>


-- 
Enrico CAPRIO, PhD
Laboratorio di Ecologia Animale
Dipartimento di Scienze della Vita e Biologia dei Sistemi
Via Accademia Albertina, 13
I - 10123 Torino
Cell. 3332134420
http://www.personalweb.unito.it/enrico.caprio/

	[[alternative HTML version deleted]]

