Tree-structured subgroup analysis for censored survival data: Validation of computationally inexpensive model selection criteria

Abdissa Negassa, Antonio Ciampi, Michal Abrahamowicz, Stanley Shapiro, Jean François Boivin

Research output: Contribution to journalArticle

39 Scopus citations

Abstract

The performance of computationally inexpensive model selection criteria in the context of tree-structured subgroup analysis is investigated. It is shown through simulation that no single model selection criterion exhibits a uniformly superior performance over a wide range of scenarios. Therefore, a two-stage approach for model selection is proposed and shown to perform satisfactorily. Applied example of subgroup analysis is presented. Problems associated with tree-structured subgroup analysis are discussed and practical solutions are suggested.

Original languageEnglish (US)
Pages (from-to)231-239
Number of pages9
JournalStatistics and Computing
Volume15
Issue number3
DOIs
StatePublished - Jul 1 2005

Keywords

  • Censored survival data
  • Model selection
  • Regression tree
  • Subgroup analysis
  • Two-stage approach

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Computational Theory and Mathematics

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