Variance Inflation Factor: As a Condition for the Inclusion of Suppressor Variable(s) in Regression Analysis

DOI: 10.4236/ojs.2015.57075   PDF   HTML   XML   6,663 Downloads   9,263 Views   Citations


Suppression effect in multiple regression analysis may be more common in research than what is currently recognized. We have reviewed several literatures of interest which treats the concept and types of suppressor variables. Also, we have highlighted systematic ways to identify suppression effect in multiple regressions using statistics such as: R2, sum of squares, regression weight and comparing zero-order correlations with Variance Inflation Factor (VIF) respectively. We also establish that suppression effect is a function of multicollinearity; however, a suppressor variable should only be allowed in a regression analysis if its VIF is less than five (5).

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Akinwande, M. , Dikko, H. and Samson, A. (2015) Variance Inflation Factor: As a Condition for the Inclusion of Suppressor Variable(s) in Regression Analysis. Open Journal of Statistics, 5, 754-767. doi: 10.4236/ojs.2015.57075.

Conflicts of Interest

The authors declare no conflicts of interest.


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