In statistics, the variance inflation factor is the ratio of variance in a model with multiple terms, divided by the variance of a model with one term alone. It quantifies the severity of multicollinearity in an ordinary least squares regression analysis. It provides an index that measures how much the variance of an estimated regression coefficient is increased because of collinearity.

A measure of the amount of multicollinearity in a set of multiple regression variables. The presence of multicollinearity within the set of independent variables can cause a number of problems in the understanding the significance of individual independent variables in the regression model. Using variance inflation factors helps to identify multicollinearity issues so that the model can be adjusted.

The variance inflation factor allows a quick measure of how much a variable is contributing to the standard error in the regression. When significant multicollinearity issues exist, the variance inflation factor will be very large for the variables involved. After these variables are identified, there are several approaches that can be used to eliminate or combine collinear variables, resolving the multicollinearity issue.

www.tandfonline.com [PDF]

… The collinearity can become worse with designs that have factors at more than two levels, because the measured differences also need to be equally spaced. The variance inflation factor (VIF) is one of the tools used to measure the degree of collinearity present for each factor …

www.tandfonline.com [PDF]

… The collinearity can become worse with designs that have factors at more than two levels, because the measured differences also need to be equally spaced. The variance inflation factor (VIF) is one of the tools used to measure the degree of collinearity present for each factor …

www.tandfonline.com [PDF]

… The collinearity can become worse with designs that have factors at more than two levels, because the measured differences also need to be equally spaced. The variance inflation factor (VIF) is one of the tools used to measure the degree of collinearity present for each factor …

www.tandfonline.com [PDF]

… The collinearity can become worse with designs that have factors at more than two levels, because the measured differences also need to be equally spaced. The variance inflation factor (VIF) is one of the tools used to measure the degree of collinearity present for each factor …

www.tandfonline.com [PDF]

… The collinearity can become worse with designs that have factors at more than two levels, because the measured differences also need to be equally spaced. The variance inflation factor (VIF) is one of the tools used to measure the degree of collinearity present for each factor …

www.tandfonline.com [PDF]

… The collinearity can become worse with designs that have factors at more than two levels, because the measured differences also need to be equally spaced. The variance inflation factor (VIF) is one of the tools used to measure the degree of collinearity present for each factor …

www.tandfonline.com [PDF]

… The collinearity can become worse with designs that have factors at more than two levels, because the measured differences also need to be equally spaced. The variance inflation factor (VIF) is one of the tools used to measure the degree of collinearity present for each factor …

www.tandfonline.com [PDF]

… The collinearity can become worse with designs that have factors at more than two levels, because the measured differences also need to be equally spaced. The variance inflation factor (VIF) is one of the tools used to measure the degree of collinearity present for each factor …

Tags:amountanalysisassetbasedbusinesscapitalcheckcorporatedefinitiondifferenceeconomiceconomicsexplainfactorfactorsfinancefinancialhongimpactindependentinflationkongmeaningmeasuremodelmultipleperformancerateresearchshowssocialstatisticsvaluesvariablevariablesvariance

A large variance inflation factor indicates that there are significant multicollinearity issues.

One approach for resolving these issues is to eliminate or combine collinear variables.

The purpose of variance inflation factor is to identify multicollinearity issues.