Dear list

 

I'm trying to model the relationship between prey capture success by fish
and fish size, density and velocity, but I’m not sure which statistical
method to use – GLMM or GLM? Capture success was collected during trials
that consisted in sending a prey every x min, which could be captured or not
by individual fish. A total of 20 prey was send in each trial. 

 

Method A: GLMM

 

I used fish.id as a random effect and the behavior of fish (0 no capture, 1-
capture) as the response variable. One of my models looks like this:

 

Model1<-glmer(capture~fish size + density
velocity+(1|fish.id.),family=binomial,data=cap)

 

 

Method B: GLM

 

The response variable was the proportion of prey captured by each fish and
one of my models:

 

Model1<-glm(prop.capture~fish size + density
velocity,family=binomial,data=cap)

 

 

I used model selection using Akaike weights to examine the performance of
each model.  Results were similar with both methods, but I think I lose a
bit of biological information if I use A: 1) I can't model average which may
mean a loss of information when I have many interpretable models as I have
with both approaches, 2) I lose the "fish size" effect which is an important
bit of biological information (i.e. larger fish have higher capture success
rates). However, A might be more appropriate for my type of data, even
though I’m not interested in variation within fish but among fish ….

 

Can anyone help?

 

Thanks in advance!

 

 

Joana Martelo, PhD Student

Centro de Biologia Ambiental

Departamento de Biologia Animal

Faculdade de Ciências, Edificio C2,5ºPiso,Sala 2.5.15B

1749-016 Lisboa, Portugal

 <http://ffishgul.fc.ul.pt/> http://ffishgul.fc.ul.pt

Por favor pense na sua responsabilidade ambiental antes de imprimir este
email 

 

 

 


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