I am relatively new to R and I would appreciate some advice on how to include both discrete and continuous predictor variables in a stepwise backward log likelihood ration logistic regression. I have a model that includes 3 continuous predictor variables (soilmois, grasscov, and ranvar) and one discrete predictor (grnsqrl) coded as 0 and 1.
The script I used was: Bdata$grnsqrl <- factor(Bdata$grnsqrl) fit2 <-logistf(data=Bdata, badger~soilmois+grasscov+ranvar+grnsqrl) summary(fit2) backward(fit2) drop1(fit2) The model summary works fine but for either backward.logistf or drop1.logistf give the error: missing value where TRUE/FALSE needed Thank you! -- View this message in context: http://r.789695.n4.nabble.com/Discrete-variables-with-logistf-tp4703403.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.