The multicollinearity illusion in moderated regression analysis

David Disatnik; Liron Sivan

doi:10.1007/s11002-014-9339-5

The multicollinearity illusion in moderated regression analysis

David Disatnik^*, Liron Sivan

^*Corresponding author for this work

Coller School of Management

Research output: Contribution to journal › Article › peer-review

Abstract

Numerous papers in the fields of marketing and consumer behavior that utilize moderated multiple regression express concerns regarding the existence of a multicollinearity problem in their analyses. In most cases, however, as we show in this paper, the perceived multicollinearity problem is merely an illusion that arises from misinterpreting high correlations between independent variables and interaction terms.

Original language	English
Pages (from-to)	403-408
Number of pages	6
Journal	Marketing Letters
Volume	27
Issue number	2
DOIs	https://doi.org/10.1007/s11002-014-9339-5
State	Published - 1 Jun 2016

Keywords

Interaction
Moderated multiple regression
Multicollinearity
Regression analysis

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/s11002-014-9339-5

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The multicollinearity illusion in moderated regression analysis

Abstract

Keywords

UN SDGs

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