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. 		 	   		  
	[[alternative HTML version deleted]]

