Hello Xiaogang, and thank you for your answer.

Your solution was indeed the way I had considered taking (after consulting
with some friends in my lab), however, I had hoped to find out if this
information (what variable effects which outcome variable) was somehow
implicitly contained within the rpart object/information.
Due to the current silence of the list, I understand that maybe taking the
approach you proposed would be better.

Thanks,
Tal



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Details:-------------------------------------------------------
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On Wed, Dec 15, 2010 at 1:03 AM, Xiaogang Su <xiaogangsu@gmail.com> wrote:

> Hi, Tal,
>
> Here is a quick way of getting around. First create two responses via
> dummy variables
>
> y1 <- ifelse(y=="a", 1, 0)
> y2 <- ifelse(y=="b", 1, 0)
>
> and then built two separate tree models for y1 and y2 separately.
>
> Hope it helps.
> Xiaogang
>
>
> On Tue, Dec 14, 2010 at 8:33 AM, Tal Galili <tal.galili@gmail.com> wrote:
> > Hi dear R-help memebers,
> >
> > When building a CART model (specifically classification tree) using
> rpart,
> > it is sometimes obvious that there are variables (X's) that are
> meaningful
> > for predicting some of the outcome (y) variables - while other predictors
> > are relevant for other outcome variables (y's only).
> >
> > *How can it be estimated, which explanatory variable is "used" for which
> of
> > the predicted value in the outcome variable?*
> >
> > Here is an example code in which x2 is the only important variable for
> > predicting "b" (one of the y outcomes). There is no predicting variable
> for
> > "c", and x1 is a predictor for "a", assuming that x2 permits it.
> >
> > How can this situation be shown using the an rpart fitted model?
> >
> > N <- 200
> > set.seed(5123)
> >
> > x1 <- runif(N)
> >
> > x2 <- runif(N)
> >
> > x3 <- runif(N)
> >
> > y <- sample(letters[1:3], N, T)
> >
> > y[x1 <.5] <- "a"
> >
> > y[x2 <.1] <- "b"
> >
> > fit <- rpart(y ~ x1+x2)
> >
> > fit2 <- prune(fit, cp= 0.07)
> >
> > plot(fit2)
> >
> > text(fit2, use.n=TRUE)
> >
> > Thanks,
> >
> > Tal
> >
> >
> >
> > ----------------Contact
> > Details:-------------------------------------------------------
> > Contact me: Tal.Galili@gmail.com |  972-52-7275845
> > Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il (Hebrew) |
> > www.r-statistics.com (English)
> >
> ----------------------------------------------------------------------------------------------
> >
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> >
> > ______________________________________________
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> > PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
>
>
>
> --
> ==============================
> Xiaogang Su, Ph.D.
> Associate Professor, Statistician
> School of Nursing, University of Alabama
> Birmingham, AL 35294-1210
> (205) 934-2355 [Office]
> xgsu@uab.edu
> xiaogangsu@gmail.com
> http://homepage.uab.edu/xgsu/
>

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