Again...thank you very much for all !!!


2014-05-14 17:13 GMT-03:00 Ben Bolker <bbolker@gmail.com>:

> On 14-05-14 08:56 AM, Carlos Barboza wrote:
> > Dear Dr. Bolker,
>
>   (note this is sent to the mixed models list, not just to me ...)
>
> > I'm working with spatial factors: sectors are spaced by kilometers, sites
> > (randomly sampled within sectors) are spaced by hundred of meters, and
> > points (randomly sampled within sites) are spaced by dozen of meters. I
> > have, 3 sectors, 3 sites within each sector and 3 points within each
> site,
> > replicated 5 times (n=135). Sectors specify a pollution gradient. So I
> want
> > to investigate the sector's effect (fixed) and the spatial variability
> > within each sector by two spatial scales, sites and points. Labels were
> > coded like your example in http://glmm.wikidot.com/faq:  (e.g. A1, A2,
> …,
> > B1, B2, …), the only difference is to include points
> (A11,A12,A13.....A33).
> > So this was my doubt:
> >
> >> model.1<- glmmadmb(total ~ sector + (1 | sector/site/point),...
> >
> > or
> >
> >> model.2<-glmmadmb(total ~ sector + (1 | site/point),...
> >
> > when I want to include all spatial variability????
>
>   Given what you have said, the second specification is correct.  The
> first includes sector, redundantly, both as a fixed effect and as a
> grouping variable for variation in intercepts.
>
> >
> > # since I want to test if a model including only sector or sector and
> > within spatial variability of each sectors, are better then a null
> model, I
> > specified this null model with the intercept only:
> >
> >> null.model<-glmmadmb(total ~ 1 ,..
>
>   Sounds reasonable, although keep in mind the issues with using
> likelihood ratio tests to test null hypotheses of zero variance ...
>
>   Ben Bolker
>
>

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