A critique is presented of the use of tree-based partitioning algorithms to
formulate classification rules and identify subgroups from clinical and ep
idemiological data. It is argued that the methods have a number of limitati
ons, despite their popularity and apparent closeness to clinical reasoning
processes. The issue of redundancy in tree-derived decision rules is discus
sed. Simple rules may be unlikely to be "discovered" by tree growing. Subgr
oups identified by trees are often hard to interpret or believe and net eff
ects are not assessed. These problems arise fundamentally because trees are
hierarchical. Newer refinements of tree technology seem unlikely to be use
ful, wedded as they are to hierarchical structures. (C) 2001 Elsevier Scien
ce Inc. Ah rights reserved.