Try looking at the help page for factor ?factor for something to start with.
-- Don MacQueen Lawrence Livermore National Laboratory 7000 East Ave., L-627 Livermore, CA 94550 925-423-1062 Lab cell 925-724-7509 On 10/5/17, 10:54 AM, "R-help on behalf of Alexandra Thorn" <r-help-boun...@r-project.org on behalf of alexandra.th...@gmail.com> wrote: I'm trying to develop a linear model for crop productivity based on variables published as part of the SSURGO database released by the USDA. My default is to just run lm() with continuous predictor variables as numeric, and discrete predictor variables as factors, but some of the discrete variables are ordinal (e.g. drainage class, which ranges from excessively drained to excessively poorly drained), but this doesn't make use of the fact that the predictor variables have a known order. How do I correctly set up a regression model (with lm or similar) to detect the influence of ordinal variables? How will the output differ compared to the dummy variable outputs for unordered categorical variables. Thanks, Alex ______________________________________________ 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. ______________________________________________ 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.