[R-sig-ME] modeling question

Ben Bolker bbolker at gmail.com
Thu Jan 26 19:59:52 CET 2017 

On Thu, Jan 26, 2017 at 9:38 AM, Joaquín Aldabe
<joaquin.aldabe at gmail.com> wrote:
> Dear Ben, it's me again


(I don't mind if you cc: me, but this is really a question to the
list. Probably better to frame it as "I sent this to the list and Ben
Bolker said ...")

> with this subject about invertebrate biomass and its
> possible effect on shorebird density. I have a couple of extra doubts about
> your recommendations:


>
> You suggested this:
>
> (1) The relationship between bird density and invert biomass, as well
> as the intercept (i.e., expected bird density at invert_biomass=0, or
> better invert_biomass=<some sensible reference quantity>).
>
> I tried a quantity considering the lowest value of the invertebrate biomass
> variable, but the model did not converge. So I wonder if I should pick this
> value or a different one?

Hmm, is this with lme or lmer?  Can you give more detail?  If it's
lmer, it's quite likely a false positive.

>
> (2) The relationship might be changing over time?
>
> lme(Bird.density~Invertebrate biomass+sample_time,
> random=~invert_biomass|Plot_identity, data=)
>
> How should I treat sample time? Is it a ordered categorical variable?

   Depends on a number of things.  Your original message suggested
that you sampled over the course of 30 days (maybe at different times
in different plots?)  If this is the case (e.g. you sampled plot 1 on
days 1, 5, 9, ... and plot 2 on days 2, 6, 10 ...) then it is probably
most sensible to treat time as a numeric variable (i.e., assume a
linear trend over days) and possibly a random effect with days as a
grouping variable (in which case you might have to switch from lme to
lmer).  If you have a small number of distinct sample days then a
categorical variable makes sense. Whether you specify it as ordered or
(default) unordered doesn't affect the overall fit of the model, just
the particular contrasts that get tested with respect to the time
variable.


>
> Thankyou very much.
>
> Joaquin
>
>
> 2017-01-16 19:49 GMT-03:00 Ben Bolker <bbolker at gmail.com>:
>>
>>
>>   Center your biomass variable on this value: either create a
>>
>>   mydata$invert_biomass_c <- mydata$invert_biomass-ref_value
>>
>> or include it directly in your formula:
>>
>>    bird_dens ~ I(invert_biomass-ref_value), ...
>>
>> On 17-01-16 05:44 PM, Joaquín Aldabe wrote:
>> > Thankyou very much Ben. Can you please suggest a way of fixing some
>> > sensible reference quantity for Invertebrate biomass?
>> > All the best,
>> > Joaquín
>> >
>> > 2017-01-16 18:59 GMT-03:00 Ben Bolker <bbolker at gmail.com
>> > <mailto:bbolker at gmail.com>>:
>> >
>> >     That seems perfectly reasonable.  There are a couple of things to
>> >     consider, although you may or may not find that your data supports
>> >     that much complexity.
>> >
>> >     (1) The relationship between bird density and invert biomass, as
>> > well
>> >     as the intercept (i.e., expected bird density at invert_biomass=0,
>> > or
>> >     better invert_biomass=<some sensible reference quantity>)
>> >
>> >     lme(Bird.density~Invertebrate biomass,
>> >     random=~invert_biomass|Plot_identity, data=)
>> >
>> >
>> >     (2) The relationship might be changing over time?
>> >
>> >     lme(Bird.density~Invertebrate biomass+sample_time,
>> >     random=~invert_biomass|Plot_identity, data=)
>> >
>> >     (3) In principle you could consider random effects of both time and
>> >     invert biomass, but that will almost certainly overwhelm your data.
>> >
>> >       Don't forget to do the standard post-fitting checks: are your
>> >     residuals *approximately* equal-variance and (even more
>> > approximately)
>> >     Normally distributed?  Is the relationship between bird density and
>> >     invert biomass *approximately* linear?  (See ?plot.lme)
>> >
>> >
>> >     On Mon, Jan 16, 2017 at 2:06 PM, Joaquín Aldabe
>> >     <joaquin.aldabe at gmail.com <mailto:joaquin.aldabe at gmail.com>> wrote:
>> >     > Dear all, I'm interested in modeling the effect of invertebrate
>> > biomass on
>> >     > the density of a grassland shorebird (they eat invertebrates). For
>> > this, I
>> >     > picked 8 plots and sampled invertebrates and birds 6 times in each
>> > plot for
>> >     > about 30 days. This is, I went to each plot and did repeated
>> > measures of
>> >     > invertebrates biomass and shorebird density separated in time by
>> > four or
>> >     > five days, as invertebrates biomass may change over time and it is
>> > expected
>> >     > that birds density change accordingly.
>> >     >
>> >     > So, I'm trying to see a general pattern of the effect of changes
>> > in biomass
>> >     > on the density of this shorebird species at a plot scale. Plot
>> > identity is
>> >     > not important; I consider them as particular events of a random
>> > process.
>> >     >
>> >     > Is this model correct:
>> >     >
>> >     > lme(Bird.density~Invertebrate biomass, random=~1|Plot_identity,
>> > data=)
>> >     >
>> >     > Thank you very much,
>> >     >
>> >     > Joaquin.
>> >     >
>> >     >
>> >     > --
>> >     > *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/joaquin.aldabe>
>> >     > <https://sites.google.com/site/perfilprofesionaljoaquinaldabe
>> >     <https://sites.google.com/site/perfilprofesionaljoaquinaldabe>>
>> >     >
>> >     >         [[alternative HTML version deleted]]
>> >     >
>> >     > _______________________________________________
>> >     > R-sig-mixed-models at r-project.org
>> >     <mailto:R-sig-mixed-models at r-project.org> mailing list
>> >     > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>> >     <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>
>> >
>> >
>> >
>
>
>
>
> --
> 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
>
>
>

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