On 19-Feb-09 10:38:50, Simon Pickett wrote: > 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]],])
So, above, you have fitted two models: m1, m2 > then compare models using anova() > anova(m1,m1b,test="F") And here you are comparing two models: m1, m1b Could this be the reason for your result? > 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. -------------------------------------------------------------------- E-Mail: (Ted Harding) <ted.hard...@manchester.ac.uk> Fax-to-email: +44 (0)870 094 0861 Date: 19-Feb-09 Time: 10:56:12 ------------------------------ XFMail ------------------------------ ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.