[R] testing effects of quantitative predictors on a categorical response variable

jferrer@ivic.ve jferrer at ivic.ve
Wed Jun 9 13:18:49 CEST 2004

Hi Avril,

I'm not sure what you want to show. Do you want to know the effects of
each variable? or just predict when you get z=A and when z=B?

In the latter case, I think that, if x and y are in the same units, you
could simply try

w <- y-x
glm1 <- glm(z ~ w,family=binomial(),trace=T)

Hope it helps,


En respuesta a / Antwort zu / Reply to:

~~   I have a small statistics question, and
~~as I'm quite new to statistics and R, I'm not
~~sure if I'm doing things correctly.
~~   I am looking at two quantitative
~~variables (x,y) that are correlated.
~~When I divide the data set according to a categorical
~~variable z, then x and y are more poorly correlated
~~when z = A than when z = B (see attached figure).
~~In fact x and y are two (correlated) predictor
~~variables and z is a categorical response variable that
~~x and y affect.
~~   I would like to use R to make some statistical
~~test to show that you seem to get z = A when
~~the value of x is much less than y, while you
~~tend to get z = B when x is approximately the same as y.
~~Can anybody tell me what I should be doing?
~~I tried a logistic regression:
~~> glm1 <- glm(z ~ y + x,family=binomial(),trace=T)
~~which gives Pr(>|z|) < 0.01 for both x and y, but
~~I'm not sure if this is valid to do, since x and y are correlated?
~~As well this test does not show that it is for values of
~~x << y that we tend to get z = A, and that for
~~values of x approx = y, that we tend to get z = B. I'm
~~not sure how to show this?
~~I'll be very grateful if anyone can help.

Dipl.-Biol. J.R. Ferrer Paris ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Laboratorio de Biología de Organismos - Centro de Ecología
   Instituto Venezolano de Investigaciones Científicas
             Apartado 21827 - Caracas 1020A
     Tel:00-58-212-5041452 --- Fax: 00-58-212-5041088
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ jferrer at ivic.ve

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