Classification and regression trees (CART) used for the exploration of prognostic factors measured on different scales

The modelling of the relationship of some response to factors measured on different scales is a common problem in various fields of application. We discuss the regression tree model in the context of general regression models and present the idea od the regression tree algorithm. In this approach all factors under consideration have to be split to binary variables, leading to a high probability of wrongly identifying as influential a variable with many splits. We propose a strategy to adjust for such an undesirable Finally, we illustrate our modification of the classification and regression tree method with data from a multicenter randomized clinical trial in patients with brain tumors.