This article describes how to compute the variance inflation factors (VIF) of linear models and generalized variance-inflation factors (GVIF) for generalized linear models to diagnose multicollinearity.
Requirements
- A Regression output for one of the following types of regressions:
- Linear
- Binary Logit
- Ordered Logit
- Poisson
- Quasi-Poisson
- NBD
Note: This feature is not compatible with multinomial logit regressions
Method
- Select the Regression output.
- Go to the object inspector > Inputs > DIAGNOSTICS >Multicollinearity Table (VIF), or go to Anything > Advanced Analysis > Regression > Diagnostics >Multicollinearity Table (VIF).
Next
How to Run Binary Logit Regression
How to Run a Generalized Linear Model
How to Run a Multinomial Logit Regression
How to Run NBD Regression in Displayr
How to Run Ordered Logit Regression
How to Run Quasi-Poisson Regression
How to Run a Stepwise Regression
How to Create a Prediction-Accuracy Table
How to Create a Goodness-of-Fit Plot
How to Test Residual Heteroscedasticity of Regression Models
How to Save Predicted Values of Regression Models
How to Save Fitted Values of Regression Models
How to Save Probabilities of Each Response of Regression Models
How to Test Residual Normality (Shapiro-Wilk) of Regression Models
How to Test Residual Serial Correlation (Durbin-Watson) of Regression Models