Hi, Thanks for the reply! I did try this...
# res is a data frame levels(res$mytypeid.f) <- c(levels(res$mytypeid.f),"mynewlevel") logreg <- glm(yesno ~ mytypeid.f + amount, data=res, family="binomial") exp(coef(logreg)) # this result shows that the new level is not included in the regression. it's probably automatically removed. I think what I want to do is identify new levels that are not in the training set, and prune those from the test set. Then I would be using the dummy variable by default, which I think is the "average", from reading this: http://www.ats.ucla.edu/stat/r/library/contrast_coding.htm Problem is, I'm not sure how to do that... -- View this message in context: http://r.789695.n4.nabble.com/GLM-What-is-a-good-way-for-dealing-with-new-factor-levels-in-the-test-set-tp4706621p4706644.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
