Problems with logarithmic transformations in regression

Richard H. McCuen, Rita B. Leahy, Peggy A. Johnson

Research output: Contribution to journalArticle

57 Scopus citations

Abstract

The power model is widely used in engineering as the structure for empirical models. The coefficients are fitted using a logarithmic transformation of the data. The logarithmic transformation leads to a biased model, which is not usually corrected for. Even when the traditional approach to eliminating the bias is used, only the intercept coefficient is changed; the other coefficients are not corrected, so they remain biased estimators. A numerical method for fitting the coefficients of the power model is discussed; the method enables the coefficients to be fit so they provide unbiased estimates and a minimum-error variance in the y-space, rather than the log y-space. The numerical method is easily modified to fit the coefficients using an objective function based on the relative errors. Examples using actual engineering data are provided.

Original languageEnglish (US)
Pages (from-to)414-428
Number of pages15
JournalJournal of Hydraulic Engineering
Volume116
Issue number3
DOIs
StatePublished - Mar 1990

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Water Science and Technology
  • Mechanical Engineering

Fingerprint Dive into the research topics of 'Problems with logarithmic transformations in regression'. Together they form a unique fingerprint.

  • Cite this