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

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DOI: 10.4236/ojs.2015.57075    5,213 Downloads   6,354 Views   Citations

ABSTRACT

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).

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

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.

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