Regression trees for analysis of count data with extra Poisson variation

This article proposes methods for fitting piecewise loglinear models to count data with an extra-Poisson variation. Both SUPPORT (Statistica Sinica, 4 (1994) 143) and GUIDE (Statistica Sinica, 12 (2002) 361) are used for splitting methods. We developed a new bootstrap resampling method performed at each node of the tree to determine the proper size of a tree. The quasi-likelihood approach is used for fitting an extra-Poisson model at each stratum to take into account the extra variability. An adjusted Anscombe residual for the extra-Poisson model is used in this procedure. Performance of the proposed method is evaluated by a Monte Carlo simulation study. The proposed method is used to investigate geographic variability in mortality rates on lung cancer as well as effects of various demographic variability. (c) 2004 Elsevier B.V. All rights reserved.