Dimension reduction and graphical exploration in regression including survival analysis

Research output: Contribution to journalArticle

15 Scopus citations

Abstract

Recent advances in dimension reduction and visualization can greatly facilitate the exploratory and diagnostic stages of a regression analysis. This paper contains an expository discussion of selected methodology that came from these advances. Various applications are described, including new results on survival regressions with censoring. All of the methodology described in this paper is available in Arc, a recently released computer program that integrates many standard regression methods with recent developments in regression graphics. Arc implementations are indicated throughout the discussion.

Original languageEnglish (US)
Pages (from-to)1399-1413
Number of pages15
JournalStatistics in Medicine
Volume22
Issue number9
DOIs
StatePublished - May 15 2003

Keywords

  • Arc
  • Central subspace
  • Principal Hessian directions
  • Sliced average variance estimation
  • Sliced inverse regression

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