Thanks for the advise. I tried predict but no matter what I do I always get an error message saying that the 'x' and 'y' differ in length. Most of my variables are also not categorical but continous of which I'm not sure how to deal with.
R procedure of a simplified model with categorical variable: model2<-glm(total$Response~total$Distance*total$Topography,binomial) xv<-seq(0,500,1) lines(xv,predict(model2,data.frame(Distance=xv,Topography=factor(rep("flat",length(xv),levels=levels(total$Topography))),type="response"))) I also tried it the way Crawley suggests in his book: tf<-rep("flat",501) yv<-predict(model2,list(Topography=factor(tf),Distance=xv),type="response") lines(xv,yv) But I still get the same error message saying that 'x' and 'y' differ in lengths. Any suggestions where the mistake might be? In the end I want to get a graph for a model like this: glm(Response~NEdist+I(NEdist^2)+Distance*Horizon+I(Distance^2)*Visibility -- View this message in context: http://r.789695.n4.nabble.com/How-to-produce-glm-graph-tp3051548p3051755.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.