Hi there,
For my hierarchical regression model, I have planned to report the VIF values to indicate collinearity. I worry that as I am including interaction terms, these values will be high. Would entering the interaction terms separately (i.e., without the proposed moderator) help with this?
Secondly, what is the recognised threshold for a critical VIF value? This stats resources states a value lower than 10 is acceptable (Hair, Joseph F., et al. Multivariate Data Analysis: A Global Perspective. 7th ed. Upper Saddle River: Prentice Hall, 2009. Print.), but some studies have standardised / mean centred the variables even at a VIF of approx 4.0. Lastly, any advice on choosing standardisation or mean centring would be greatly appreciated.
Thanks a lot,
Esther
Hello Esther,
some kind colinearity is a usal consquence in testing interaction effects. The only solution is to have a high enough N to compensate for the increase in standard errors.
Leaving out the linear part (the moderator) hinders to test the interaction effect.
HTH
--Holger
Great, thanks a lot Holger. And if the VIF values are high should I try standardising the variables to see if this alters the p-values?
Standardizing will not do anything substantial:
Echambadi, R., & Hess, J. D. (2007). Mean-centering does not alleviate collinearity problems in moderated multiple regression models. Marketing Science, 26(3), 438-445.
Best,
--Holger
Hello Esther Curtin
Multicollinearity makes some of the significant variables under study to be statistically insignificant:Article Detecting Multicollinearity in Regression Analysis
Good Luck
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