Regression modelMulticollinearity diagnostics

Variance Inflation Factor (VIF)

The Variance Inflation Factor (VIF) is a scalar diagnostic statistic proposed by Donald Marquardt (1970) that quantifies how much the variance of an estimated regression coefficient increases due to linear dependence—multicollinearity—among the predictors in an ordinary least squares model. It is routinely applied in econometrics, social science, and biomedical research whenever analysts suspect that two or more independent variables move together closely enough to destabilize coefficient estimates.

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Sources

  1. Marquardt, D. W. (1970). Generalized inverses, ridge regression, biased linear estimation, and nonlinear estimation. Technometrics, 12(3), 591–612. DOI: 10.1080/00401706.1970.10488699

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Referenced by

ScholarGateVariance Inflation Factor (Variance Inflation Factor (VIF)). Retrieved 2026-06-04 from https://scholargate.app/en/econometrics/variance-inflation-factor