[R] working with ordinal predictor variables?

[Bert Gunter]

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.thorn at 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
>
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