Hi. I am a grad student and I'm currently using the MOB function in the R party
package and I had a question. I am working on an environmental problem with
about 100 predictors. I am having trouble determining which predictors to use
for regression and which for partitioning, is there any sort of method to
determine this? Does it cause problems if a variable is used for both
regression and partitioning? I attempted to pre-screen the variables using
stepwise linear regression and I used the selected variables for regression and
all others for partitioning. However this lead to the model only having one
node. Any suggestions would be very much appreciated, thanks.
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