[R-sig-ME] GLMM for data with many zeros: poisson, lognormal-poisson or zero-inflated?
Alicia Valdés
aliciavaldes1501 at gmail.com
Thu May 12 12:28:21 CEST 2011
Dear Ben,
Thanks for your response.
Looking at what you said, the variance in my random factor "site" is
nearly zero in most of the cases (the higher value is 0.1). Do you
think that then I can say that differences in site are not important?
Because I was thinking of just removing "site" from the model and then
fit a GLM instead of GLMM (as I will have only fixed effects).
What do you mean when you say that "if the means are low enough then
zero-inflation may not be necessary"? Do you refer to the means of the
"y" values without zeros? And which value should I take as "low
enough"? I believe that the means of the response variable are around
2 with the zero values included, and around 3-4 without the zeros. Is
it low enough to not include zero-inflation? Anyway, if I remove the
random factor, I will try to fir a zero-inflated GLM with zeroinfl in
pscl package, and compare it with a poisson or negative binoimial
model. Should I have any problem in comparing AIC between these
different kinds of models?
I am still a bit confused about overdispersion. You said that in order
to evaluate if there was overdispersion in my model, I should look at
the residual deviance or sum of squared Pearson residuals, but these
values are not given by lmer. I only got a "deviance" value. How can I
calculate these values, and which threshold should I consider in order
to say that I have (or not) overdispersion in my data?
The "revisions" in my data are just temporal repetitions of the
sampling. I mean, I did different samplings of the same experimental
units in different dates, and I call each of these samplings a
"revision". Anyway, I think that fitting a model for each revision
should be fine, because I can compare the significant factors between
them, as I don't have any specific hypothesis about how the effects
should change temporally.
Again, thank you very much for your time and suggestions!
Alicia Valdés Rapado
PhD Student
Dpto. Biología Organismos y Sistemas - Unidad de Ecología
Universidad de Oviedo
España - Spain
e-mail: valdesalicia.uo at uniovi.es
El 5 de mayo de 2011 11:53, Alicia Valdés <aliciavaldes1501 at gmail.com> escribió:
>
> I am sorry, one of the colummns of the example data was oddly
> displaced. Here it should be right (I hope).
>
> rev site species repl cover treat seedlings
>
> 1 1 0 1 low A
> 3
>
> 1 1 0 1 low C
> 0
>
> 1 1 0 1 low E
> 0
>
> 1 1 0 2 low A
> 5
>
> 1 1 0 2 low C
> 0
>
> 1 1 0 2 low E
> 3
>
> 1 1 0 3 high A
> 1
>
> 1 1 0 3 high C
> 0
>
> 1 1 0 3 high E
> 0
>
> 1 1 0 4 high A
> 0
>
> 1 1 0 4 high C
> 0
>
> 1 1 0 4 high E
> 0
>
> 1 1 1 1 low A
> 2
>
> 1 1 1 1 low C
> 0
>
> 1 1 1 1 low E
> 4
>
> 1 1 1 2 low A
> 0
>
> 1 1 1 2 low C
> 0
>
> 1 1 1 2 low E
> 1
>
> 1 1 1 3 high A
> 0
>
> 1 1 1 3 high C
> 0
>
> 1 1 1 3 high E
> 0
>
> 1 1 1 4 high A
> 2
>
> 1 1 1 4 high C
> 0
>
> 1 1 1 4 high E
> 0
>
> 1 2 0 1 low A
> 0
>
> 1 2 0 1 low C
> 0
>
> 1 2 0 1 low E
> 0
>
> 1 2 0 2 low A
> 0
>
> 1 2 0 2 low C
> 0
>
> 1 2 0 2 low E
> 0
>
>
> Alicia Valdés Rapado
> PhD Student
> Dpto. Biología Organismos y Sistemas - Unidad de Ecología
> Universidad de Oviedo
> España - Spain
> e-mail: valdesalicia.uo at uniovi.es
--
Alicia Valdés Rapado
Antes de imprimir este e-mail, piensa bien si es necesario hacerlo.
Una tonelada de papel implica la tala de 15 árboles. Cuida el medio
ambiente.
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