R help - Feb 2007 - Problem with party and ordered factors

Hi All,

i've got a problem using the ctree function of the party package. I've
searched around a lot but couldn't manage it.
I've got an ordered factor as response. As far as i know i have to use
scores to be able to use this ordered factor. But if i do so i get a tree
which predicts all observations as the first level of my ordered factor.

In order to test if i did anything wrong i tried the example of Torsten
Hothorn, Kurt Hornik and Achim Zeileis described in the documentation
party: A Laboratory for Recursive Part(y)titioning

There i got the same problem. I execute the following
code:
> data("mammoexp", package = "party")
> mtree <- ctree(ME ~ ., data = mammoexp, scores = list(ME = 1:3, SYMPT
1:4, DECT = 1:3))
> plot(mtree)
Beside getting one waring everthing's ok. But when i excute
summary(predict(mtree)) the result is:
 Never Within a Year   Over a Year
  412             0             0

So now i'm stuck. Am i doing anything wrong? I'm using R 2.4.1 and all
packages are uptodate.

Thanks in advance for your help.

Sincerely yours
Christoph

Christoph:
> I've got an ordered factor as response. As far as i know i have to use
> scores to be able to use this ordered factor.
If you want to exploit the ordering in the statistical tests (used for
variable selection in CTree), a natural approach is to use a
linear-by-linear test with scores assigned to the ordered levels of your
factor. That's what the example below does.
> But if i do so i get a tree
> which predicts all observations as the first level of my ordered factor.
That is not due to the factor being ordered. It results simply from the
fact that more than half of the observations have "Never" in the
variable
ME.
> There i got the same problem. I execute the following code:
> > data("mammoexp", package = "party")
> > mtree <- ctree(ME ~ ., data = mammoexp, scores = list(ME = 1:3,
SYMPT > 1:4, DECT = 1:3))
> > plot(mtree)
If you look at this picture, you can see that majority voting in each node
will result in the prediction "Never".
> So now i'm stuck. Am i doing anything wrong?
Nothing.
If you want to see how the distribution in each node changes, you can
look at
  treeresponse(mtree)
> I'm using R 2.4.1 and all packages are uptodate.
Not anymore, I just uploaded a new "party" version to CRAN ;-))

Best wishes,
Z