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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