Hi all,

This could be naivety/stupidity on my part rather than a problem with model output, but here goes....

I have fitted a fairly simple model 

m1<-glm(count~siteall+yrs+yrs:district,family=quasipoisson,weights=weight,data=m[x[[i]],])

I want to know if yrs (a continuous variable) has a significant unique effect in the model, so I fit a simplified model with the main effect ommitted...

m2<-glm(count~siteall+yrs:district,family=quasipoisson,weights=weight,data=m[x[[i]],])

then compare models using anova()
anova(m1,m1b,test="F")

Analysis of Deviance Table

Model 1: count ~ siteall + yrs + yrs:district
Model 2: count ~ siteall + yrs:district
  Resid. Df Resid. Dev   Df Deviance F Pr(>F)
1      1936      75913                       
2      1936      75913    0        0         
> 

The d.f.'s are exactly the same, is this right? Can I only test the significance of a main effect when it is not in an interaction? 

Thanks in advance,

Simon.






Dr. Simon Pickett
Research Ecologist
Land Use Department
Terrestrial Unit
British Trust for Ornithology
The Nunnery
Thetford
Norfolk
IP242PU
01842750050

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