This article may be helpful, at least to get you started: https://www.r-bloggers.com/ordinal-data/
Cheers, Boris > On Oct 5, 2017, at 3:35 PM, Bert Gunter <bgunter.4...@gmail.com> wrote: > > I would consider this is a question for a statistics forum such as > stats.stackexchange.com, not R-help, which is about R programming. They do > sometimes intersect, as here, but I think you need to *understand what > you're doing* before you write the R code to do it. > > Obviously, IMO. > > Cheers, > Bert > > > > > Bert Gunter > > "The trouble with having an open mind is that people keep coming along and > sticking things into it." > -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) > > On Thu, Oct 5, 2017 at 10:54 AM, Alexandra Thorn <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. >> > > [[alternative HTML version deleted]] > > ______________________________________________ > 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.
