[R] a ratio-variable predictor

Greg Snow Greg.Snow at imail.org
Thu Dec 18 16:30:13 CET 2008

A good article to read before using ratios is:

Kronmal, RA. Spurious Correlation and the Fallacy of the Ratio Standard Revisited. Journal of the Royal Statistical Society. Series A, Vol 156, No. 3 (1993), 379-392.

It shows some of the traps that misusing ratios can lead to along with strategies for avoiding those traps.

Hope this helps,

Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org

> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of Jeroen Ooms
> Sent: Thursday, December 18, 2008 3:03 AM
> To: r-help at r-project.org
> Subject: [R] a ratio-variable predictor
> Maybe this is more of a statistical question than an R question, but I
> am
> going to ask it anyway :) Cortisol and Testosteron are known to
> interact in
> the body, and some literature suggest that especially the ratio between
> the
> two is a good predictor. So I want to add the ratio predictor
> (y~cort/test)
> to a glm, and later a multilevel model, however I have no experience
> with
> ratio variables.
> Intuitively, I would think that a ratio is very similar to an
> interaction
> effect, only with an inverse scale for the second term (cort* 1/test).
> However, I found that even more than with normal interaction effects,
> the
> scaling of the variables becomes important. Furthermore there is the
> obvious
> problem (which is not too big of a problem in my case), of values that
> are
> close to zero on the second term.
> So what is an appropriate way to incorporate a ratio-predictor? Any
> tips on
> R procedure/package that I could use, or any other experiences with
> ratio-predictors are welcome.
> --
> View this message in context: http://www.nabble.com/a-ratio-variable-
> predictor-tp21069805p21069805.html
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