In recent years a number of nonparametric regression-type statistical procedures have been developed. Classification and regression trees (CART) is one such method that can be used as a classifier for a discrete-valued response variable or as a regression model for a continuous response variable. Advantages of CART over many other methods are its ability to include a relatively large number of independent variables and to identify complex interactions among these variables. A brief description of the CART procedure is given, and its application as a classifier and as a regression model to highway safety analyses is illustrated.
Determining late predictors of outcome for acetaminophen- induced acute liver failure using classification and regression tree modeling analysis