Multicollinearity in marketing models: Diagnostics and remedial measures

Chezy Ofir*, André Khuri

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

30 Scopus citations

Abstract

The problem of multicollinearity in linear models is reviewed. Diagnostic measures for detection, analysis of the effects, and localization of multicollinearity are presented. It is recommended that OLS estimates should not be used without a proper diagnostic. The traditional remedial measures, i.e., omission of variables from the model and principal component regression, are critically discussed along with more recent methods. Ridge regression is presented, and several methods for selecting the biasing parameter in ridge regression are introduced. The procedures are illustrated with data taken from the marketing literature and evaluated for their potential usefulness in handling multicollinearity.

Original languageEnglish
Pages (from-to)181-205
Number of pages25
JournalInternational Journal of Research in Marketing
Volume3
Issue number3
DOIs
StatePublished - 1986

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