[R-sig-eco] Re : guidance required (GLM?)

[Gavin Simpson]

On Wed, 2011-08-24 at 11:16 +0100, momadou sow wrote:
> Hi,
> With glm, you add the binomial family:

In general, no you don't - a GLM is far more than a logistic regression.
Otherwise, why would glm() allow for more families than just binomial?

As biomass is positive (or at least non-negative) and likely to exhibit
a non-constant mean-variance relationship, lm(log(biomass) ~ ....) or
glm(biomass ~ ...., family = Gamma) might be more appropriate. For the
latter you might need to investigate the various link function options.

HTH

G

> model<-glm(biomass~Shore*Raked*Species+Shore*Fished*Species,family=binomial)
> model
> 
> 
> De: Christopher Cesar <C.Cesar at apemltd.co.uk>
> : "r-sig-ecology at r-project.org" <r-sig-ecology at r-project.org>
> Envoy le : Mercredi 24 Aot 2011 12h02
> Objet: [R-sig-eco] guidance required (GLM?)
> 
> Hi all,
> 
> I have carried out experimental removal of bivalves at 2 intertidal shores. Bivalves were removed by raking of surface sediments. I wish compare the biomass values of for a total of 8 species between the 2 shores
> 
> My 3 treatments are: Undisturbed Controls (Cont), Procedural Controls (Proc) and Experimetnally Fished (Fished).
> 
> As Fished and Proc have both experienced disturbance, I set the model using 2 factors as follows:
> 
>  Controls Procedural Fished
> Raked 0  1  1
> Fished0  0  1
> 
> As a newcomer to R (& stats!), I am unsure as to how to proceed.
> 
> i am currently adopting the approach
> 
> model<-glm(biomass~Shore*Raked*Species+Shore*Fished*Species)
> 
> And then run post-hoc adjusted pairwise comparisons between signifcant terms.
> 
> Does this look OK to you guys?
> 
> Many, many thanks
> 
> Chris
> 
> 
> 
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> 
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