Graphics for regressions with a binary response

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Central dimension-reduction subspaces, which characterize the dependence of a response variable on one or more predictors, are developed and then used to guide the construction and interpretation of graphics for regression problems with a binary response variable. Graphical methods requiring neither a link function nor residuals are suggested for both development and criticism of model components implied by the central dimension-reduction subspace.

Original languageEnglish (US)
Pages (from-to)983-992
Number of pages10
JournalJournal of the American Statistical Association
Issue number435
StatePublished - Sep 1 1996


  • Dimension-reduction subspaces
  • Graphical regression
  • Logistic regression
  • Sliced inverse regression

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