A reviewer recently remarked to me that, due to my data being constrained to not fall below zero, a generalized linear model with a negative binomial error (or poisson) with a log link would be more appropriate for fitting my model. I ran it in R with glm.nb() and got results that matched just using lm on log transformed data pretty well. However, R indicated some warnings. I checked warnings(), and saw a list of warnings as follows:
Warning messages: 1: non-integer x = 0.254825 I got the same error when trying to use the poisson family. My data is indeed continuous, not discrete (lots of non-integers). Does this mean that the model was not fit properly? Was data dropped when fitting the model? Is there an option to deal with this that I have overlooked? It would seem all is in order, but i just wanted to make sure. Thanks! Thanks. -Jarrett ______________________________________________ [email protected] 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.
