Re : guidance required (GLM?)
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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