Variance Inflation Factor Logistic Regression. If the degree of correlation is high enough between variables it can cause problems when fitting and interpreting the regression model. Run a multiple regression.
Mar 11 2018 For a given predictor p multicollinearity can assessed by computing a score called the variance inflation factor or VIF which measures how much the variance of a regression coefficient is inflated due to multicollinearity in the model. The VIF of a predictor is a measure for how easily it is predicted from a linear regression using the other predictors. The VIF is just 1 1- R2.
Sep 10 2012 Before examining those situations lets first consider the most widely-used diagnostic for multicollinearity the variance inflation factor VIF.
The VIF is just 1 1- R2. The variance inflation factor is only about the independent variables. Steps for Implementing VIF. Multicollinearity inflates the variance and type II error.
