Unbiased variable selection for classification trees with multivariate responses

A variable selection scheme is proposed for constructing multivariate classification trees. It utilizes conditional independence test derived from hierarchical loglinear model for three-way contingency table to control selection bias. Furthermore, it is compared with some existing selection methods in terms of selection power. Simulation results show that our method is unbiased and has better selection power.