[R-sig-ME] glmm question

[Ken Beath]

I think you would be better off to start with a mixed effects model with a
random effect for site and a fixed effect for year.

All a random effect is doing is to model the correlation between responses
allowing for other variables, in other words the residuals, by conditioning
on a variable that is unobserved. For the years there are only 3 so it is
just as easy or easier to model them using a known variable, the actual
year. It is also difficult to think of them as a random sample of years.
Now for the sites you would expect the same, that the 3 measurements within
a site, representing the 3 years would be correlated. Now it is reasonable
to model them using a random effect, as otherwise there would need to be a
fixed effect for each site, a large number of parameters. It is possible
that this random effect has variance zero then the model reverts to a
standard glm.

On 14 May 2015 at 22:55, Joaquín Aldabe <joaquin.aldabe at gmail.com> wrote:

> Thanks a lot Ken for your response. I had decided to use mix model with
> random effects because I have repeated measures in each field (one per
> year). If I perform a glm, how can I manage the pseudoreplication?
> (repeated counts on the same field)
>
> I have one data per field per year. So, no hierarchical or nested
> structure of the data. Can I use field as a random effect anyway?
>
> Thanks a lot for your help.
>
> Cheers,
> Joaquín.
>
> 2015-05-13 19:17 GMT-03:00 Ken Beath <ken.beath at mq.edu.au>:
>
> Having a random effect with only 3 levels is not recommended, it usually
>> gives problems fitting. There are also some philosophical questions about
>> its use as a random effect.
>>
>> A random effect for field is reasonable, but you may be fitting too many
>> parameters. With only 57 observations it is easy to overfit the models, and
>> a standard linear model may be all that is necessary.
>>
>> On 14 May 2015 at 07:15, Joaquín Aldabe <joaquin.aldabe at gmail.com> wrote:
>>
>>> Hello, this is Joaquín Aldabe from Uruguay. I´m trying to model shorebird
>>> counts (Buff breasted Sandpiper, BBSA) with glmm (using lme4 package),
>>> using continuous variables (grass height, field area, forest cover) and
>>> one
>>> factor variable (presence/absence of other shorebird species: American
>>> Golden Plover, AMGP). I sampled 19 fields during three years in December.
>>> I´m interested in identifying predictors correlated with BBSA counts. I
>>> used Year as a random effect as I´m not interested in Year as a fix
>>> effect
>>> and because fields were counted three times (pseudoreplication).
>>>
>>> The model doesn´t converge, and the output showed that the factorial
>>> variable has not a significant effect. This is weird as in every field I
>>> observed the Buff breasted Sandpiper I also observed the other
>>> species. When I take AMGP out, the model runs ok.
>>>
>>> This is the model I´m trying to run:
>>>
>>>
>>> mysub3.3<-glmer(BBSA~Grass_height+Field_area+Field_enclosure_700m+Grass_height*Field_enclosure_700m+fAMGP+(1|fYear),family="poisson",
>>> data=mysub3.2)
>>>
>>> continuous variables were scaled.
>>>
>>> I can send de data frame if somebody is interested.
>>>
>>> Thanks in advanced for helping me on my master thesis.
>>>
>>> Cheers,
>>>
>>> Joaquín.
>>>
>>> --
>>> *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
>>>
>>
>>
>>
>> --
>>
>> *Ken Beath*
>> Lecturer
>> Statistics Department
>> MACQUARIE UNIVERSITY NSW 2109, Australia
>>
>> Phone: +61 (0)2 9850 8516
>>
>> Building E4A, room 526
>> http://stat.mq.edu.au/our_staff/staff_-_alphabetical/staff/beath,_ken/
>>
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>> This message is intended for the addressee named and may contain
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>>
>>
>
>
> --
> *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>
>
>


-- 

*Ken Beath*
Lecturer
Statistics Department
MACQUARIE UNIVERSITY NSW 2109, Australia

Phone: +61 (0)2 9850 8516

Building E4A, room 526
http://stat.mq.edu.au/our_staff/staff_-_alphabetical/staff/beath,_ken/

CRICOS Provider No 00002J
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