Transforming a response variable for linearity

R. Dennis Cook, Sanford Weisberg

Research output: Contribution to journalArticlepeer-review

34 Scopus citations


SUMMARY: We consider the problem of choosing a transformation t(y) of a univariate response variable y so that the regression function E{t(y)| x}is linear in the predictor vector x. Let y be the fitted values from a linear regression of y on x. Given a few simple assumptions, we show that the plot with y on the horizontal axis and y on the vertical axis can be used to visualise the needed transformation t(y). A smoother can then be used as an aid to assessing t(y) visually.

Original languageEnglish (US)
Pages (from-to)731-737
Number of pages7
Issue number4
StatePublished - Dec 1994


  • Box-Cox transformation
  • Elliptical distribution
  • Graphics
  • Regression

Fingerprint Dive into the research topics of 'Transforming a response variable for linearity'. Together they form a unique fingerprint.

Cite this