Thanks a lot for your anwers. To Ben Bolker : I am trying to perform an ordinal logistic regression to predict an Y 3-class variable, having observed 3 continous predictors V1, V2, V3. With random data my code would be something like :
# simulate 10 observations of 3 independant N(0,1) predictors X=rmvnorm(10,rep(0,3)) # variable to predict Y=c(1,1,1,2,2,2,3,3,3,3) # create data frame A=as.data.frame(cbind(X,Y)) # turn Y into class variable A$Y=as.factor(A$Y) # perform logisitic regression glm(Y~V1+V2+V3,A,family="binomial") As only one intercept is returned, it seems indeed that a 2-class model has been performed instead, as said by zachmor. Although I solved my problem by using polr instead of glm, I'd like to understand what glm does in such a case since it gave me better well-classification rates with the predict function. Thanks a lot again ! -- View this message in context: http://r.789695.n4.nabble.com/glm-prediction-of-a-factor-with-several-levels-tp2300793p2302078.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.
