[R] a ratio-variable predictor

[Jeroen Ooms]

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.
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