9. Regression Trees

  1. Bee Choo Tai1 and
  2. David Machin2

Published Online: 11 OCT 2013

DOI: 10.1002/9781118721957.ch9

Regression Methods for Medical Research

Regression Methods for Medical Research

How to Cite

Tai, B. C. and Machin, D. (2013) Regression Trees, in Regression Methods for Medical Research, John Wiley & Sons Ltd, Oxford. doi: 10.1002/9781118721957.ch9

Author Information

  1. 1

    Saw Swee Hock School of Public Health, National University of Singapore and National University Health System; Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore

  2. 2

    Medical Statistics Unit, School of Health and Related Sciences, University of Sheffield; Cancer Studies, Faculty of Medicine, University of Leicester, Leicester, UK

Publication History

  1. Published Online: 11 OCT 2013
  2. Published Print: 29 NOV 2013

ISBN Information

Print ISBN: 9781444331448

Online ISBN: 9781118721957

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Keywords:

  • continuous covariates;
  • regression trees;
  • tree pruning

Summary

This chapter describes the use of regression trees to help identify, among patients with a particular disease or condition, homogeneous subgroups each with an identifiable but different prognosis. The aim of establishing the groups is to tailor subsequent treatment and/or care in order to improve the ensuing outcome. The classification consists of a treelike structure beginning with a single mother or root node which is split into branches to form intermediate and/or terminal nodes referred to variously as offspring nodes, daughter or son nodes, or leaf. The root node represents all patients in the study, whereas the offspring nodes correspond to (relatively) homogeneous subgroups of patients that are identified based on specific covariate information. Details of how the tree growing process is curtailed, using a tree pruning procedure, as well as difficulties associated with the regression tree approach are included.