# Regression - Diagnostic - Multicollinearity Table (VIF) extension

Create a table containing variance inflation factors (VIF) to diagnose multicollinearity

Computes the variance inflation factors (VIF) of linear models and generalized variance-inflation factors (GCIF) for generalized linear models. See the blog for an introduction to VIFs.

## Example

The below table contains the output from running this QScript on a Regression - Binary Logitbinary logit output.

## Technical details

A score of 10 or above indicates high multicollinearity.

## Acknowledgements

Uses the vif function from the car package.

## References

Fox, J., & Monette, G. (1992). Generalized collinearity diagnostics. Journal of the American Statistical Association, 87(417), 178-183.

Bock, T. (2018, April 6). What are Variance Inflation Factors (VIFs)? [Blog post]. Retrieved from https://www.displayr.com/variance-inflation-factors-vifs/.

## Code

includeWeb("QScript R Output Functions");

const menu_location = "Regression > Diagnostic > Multicollinearity Table (VIF)";