[R-sig-ME] mixed model?

[Evan Palmer-Young]

There is a thorough but readable discussion of the fixed-or-random
consideration at the glmm wiki.
http://glmm.wikidot.com/faq, administrated by Prof. Bolker.
See the heading:
Should I treat factor xxx as fixed or random?
You'll also find plenty of useful tips for model coding and
troubleshooting, consideration of p-values, and a separate page for package
comparison.
http://glmm.wikidot.com/pkg-comparison

On Tue, May 2, 2017 at 1:56 PM, Joaquín Aldabe <joaquin.aldabe at gmail.com>
wrote:

> Thanks Ben. In this case I considered grass height as continuous. Is it
> fine to consider year as random effect with only 4 years?
> Best,
> Joaquín
>
> 2017-05-02 14:49 GMT-03:00 Ben Bolker <bbolker at gmail.com>:
>
>> Minor correction: if GrassHeight is a continuous variable then you
>> need (GrassHeight|Field) to model the among-Field variation in the
>> effect of grass height.  If GrassHeight is categorical, then
>> (GrassHeight|Field) will also work, but it will fit an unstructured
>> variance-covariance model (n*(n+1)/2 parameters for an n-level
>> categorical predictor), whereas (1|Field/GrassHeight) would fit a
>> (positive) compound-symmetric model for the variation in grass height
>> effects among fields (2 parameters instead of n*(n+1)/2)
>>
>> On Tue, May 2, 2017 at 1:36 PM, Joaquín Aldabe <joaquin.aldabe at gmail.com>
>> wrote:
>> > Thankyou very much Evan. I´ll try that!
>> > Cheers,
>> > Joaquín.
>> >
>> > 2017-05-02 14:17 GMT-03:00 Evan Palmer-Young <ecp52 at cornell.edu>:
>> >
>> >> Joaquin,
>> >> It looks like you could use Year and Field as random effects, since
>> there
>> >> might be variation in bird abundance across years, and similarly,
>> variation
>> >> across fields.
>> >>
>> >> So in this case your model is
>> >> Birdmodel<- glmer(Presence~ GrassHeight * ForestCover + (1|Year) +
>> >> (1|Field), data=BirdData, family =                  "binomial")
>> >>
>> >> Alternatively you could use Year as a fixed effect, if you are
>> interested
>> >> in particular years.
>> >> Another option is to include interaction terms as random effects, eg
>> >> (1|Field:GrassHeight), to allow the effect of GrassHeight to vary
>> across
>> >> fields.
>> >>
>> >>
>> >> On Fri, Apr 28, 2017 at 9:32 AM, Joaquín Aldabe <
>> joaquin.aldabe at gmail.com>
>> >> wrote:
>> >>
>> >>> Dear all, I'm analysing bird presence/absence in 16 grassland fields
>> over
>> >>> 4
>> >>> seasons (different years) and want to know the effect of grass height
>> and
>> >>> forest cover on presence/absence of the species. Grass height varied
>> among
>> >>> season but not forest cover in each field. So we have a spatial
>> dimension
>> >>> and a time dimension. I tried a binomial glm but wonder if I should
>> use
>> >>> generalized linear mixed models with field identity as the random as I
>> >>> have
>> >>> repeated measures (bird counts) in each field.
>> >>>
>> >>> I appreciate your opinion.
>> >>>
>> >>> Thanks in advanced,
>> >>>
>> >>> Joaquin Aldabe.
>> >>>
>> >>> --
>> >>> *Joaquín Aldabe*
>> >>>
>> >>> *Grupo Biodiversidad, Ambiente y Sociedad*
>> >>> Centro Universitario de la Región Este, Universidad de la República
>> >>> Ruta 15 (y Ruta 9), Km 28.500, Departamento de Rocha
>> >>>
>> >>> *Departamento de Conservación*
>> >>> Aves Uruguay
>> >>> BirdLife International
>> >>> Canelones 1164, Montevideo
>> >>>
>> >>> https://sites.google.com/site/joaquin.aldabe
>> >>> <https://sites.google.com/site/perfilprofesionaljoaquinaldabe>
>> >>>
>> >>>         [[alternative HTML version deleted]]
>> >>>
>> >>> _______________________________________________
>> >>> R-sig-mixed-models at r-project.org mailing list
>> >>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>> >>
>> >>
>> >>
>> >>
>> >> --
>> >> Evan Palmer-Young
>> >> PhD candidate
>> >> Department of Biology
>> >> 221 Morrill Science Center
>> >> 611 North Pleasant St
>> >> Amherst MA 01003
>> >> https://scholar.google.com/citations?user=VGvOypoAAAAJ&hl=en
>> >> https://sites.google.com/a/cornell.edu/evan-palmer-young/
>> >> epalmery at cns.umass.edu
>> >> ecp52 at cornell.edu
>> >>
>> >
>> >
>> >
>> > --
>> > *Joaquín Aldabe*
>> >
>> > *Grupo Biodiversidad, Ambiente y Sociedad*
>> > Centro Universitario de la Región Este, Universidad de la República
>> > Ruta 15 (y Ruta 9), Km 28.500, Departamento de Rocha
>> >
>> > *Departamento de Conservación*
>> > Aves Uruguay
>> > BirdLife International
>> > Canelones 1164, Montevideo
>> >
>> > https://sites.google.com/site/joaquin.aldabe
>> > <https://sites.google.com/site/perfilprofesionaljoaquinaldabe>
>> >
>> >         [[alternative HTML version deleted]]
>> >
>> > _______________________________________________
>> > R-sig-mixed-models at r-project.org mailing list
>> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>
>
>
>
> --
> *Joaquín Aldabe*
>
> *Grupo Biodiversidad, Ambiente y Sociedad*
> Centro Universitario de la Región Este, Universidad de la República
> Ruta 15 (y Ruta 9), Km 28.500, Departamento de Rocha
>
> *Departamento de Conservación*
> Aves Uruguay
> BirdLife International
> Canelones 1164, Montevideo
>
> https://sites.google.com/site/joaquin.aldabe
> <https://sites.google.com/site/perfilprofesionaljoaquinaldabe>
>
>
>
>


-- 
Evan Palmer-Young
PhD candidate
Department of Biology
221 Morrill Science Center
611 North Pleasant St
Amherst MA 01003
https://scholar.google.com/citations?user=VGvOypoAAAAJ&hl=en
https://sites.google.com/a/cornell.edu/evan-palmer-young/
epalmery at cns.umass.edu
ecp52 at cornell.edu

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