[R-sig-Geo] spatial GLM using glmmPQL

[Anne GOARANT]

Hi List,
I have observations of insect counts and environmental variables. My 
first goal was to compute a GLM to explain the insect counts with the 
environment. The thing is that my insect counts are not spatially 
independant and show spatial autocorrelation (a spherical variogram 
model can be fit to the data).
So I intend to compute the same GLM model and taking into account the 
spatial autocorrelation. The final objective would be to compare both 
model (spatial and non spatial and check which one is the best).
I read that a way to do a spatial GLM is using the glmmPQL function of 
MASS and putting all the observations in the same group for the random 
effect (Dorman, Ecography 30, 2007).  I was wondering if the "non 
computed" Log-Likelihood value (but it can be computed by changing a 
line code in the glmmPQL code function) is correct. I did some trials to 
compare the model outputs for the same dataset for glm and glmmPQL (with 
all the observations in the same group) and it gave me the same 
estimated parameters. It also gave me the same Log-Likelihood for both 
methods.
Do you have any idea if the Log-Likelihood from glmmPQL is correct when 
one considers all the data in the same group for the random effect?
Is there any other methods to do what I want (comparison of spatial and 
non-spatial GLM)?
Thanks for your help.
Anne



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