Using classification and regression trees (CART) to support worker decision making

Michelle A. Johnson, C. Hendricks Brown, Susan J. Wells

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Several approaches can be taken to predict case membership in the classes of a dependent variable. Classification and regression trees (CART) analysis has been cited repeatedly as a powerful nonparametric approach in fields where classification or prediction are of concern. To test CART's utility in a social work setting, the authors conducted a secondary analysis of data collected in a national study of child protective services screening practices to identify factors involved with worker decisions to investigate child maltreatment reports. The CART analysis revealed complex interaction effects previously unobserved in the logistic regression. Comparisons of CART with traditional statistical approaches and other tree-based programs are presented.

Original languageEnglish (US)
Pages (from-to)19-29
Number of pages11
JournalSocial Work Research
Volume26
Issue number1
DOIs
StatePublished - Mar 2002

Keywords

  • Child protective services
  • Classification and regression trees
  • Decision making
  • Decision trees
  • Screening

ASJC Scopus subject areas

  • Social Sciences (miscellaneous)

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