[R-sig-Geo] spGLM unexpectedly large sill values

[Sama Winder]

Hi all,

I am running several fairly complicated presence/absence (binary)
models, each of which includes ~700 data points and between 8 and 13
predictor variables (a mix of continuous and factor variables).

I'm using logistic regression, and first fit these without spatial
effects using glm(). Since we're concerned about residual spatial
autocorrelation, I also added spatial effects (with an exponential
correlation structure) in spGLM. After a few attempts and many
(500,000) iterations, these appear to be converging quite nicely.

However, the sigma^2 values are much bigger than we expected (35, 50,
100). As a result (I suspect), my parameter coefficients are also much
more extreme than they were in the non-spatial models.   For example,
without the spatial term my coefficients ranged from about -1.5 to
1.5, and now they range from -5 to 7. Since this is on the logistic
scale, these result in nearly perfect 0 or 1 predicted probabilities.

This feels like something has gone wrong, but I'm having trouble
placing my finger on exactly what. If not, what is the interpretation?
(As a side note, the phi values are within the range we expected).

Any insights would be greatly appreciated!

Thanks,
Sama

Sama Winder
MS Statistics
University of Alaska, Fairbanks