Collinearity Diagnostics

Colinearity diagnostics table showing eigenvalues and condition index values. Only two eigenvalues are near zero and none of the condition index values are greater than 10. — Figure 1. Collinearity diagnostics table

The eigenvalues and condition indices are vastly improved relative to the original model.

Coefficients table showing zero-order, partial and part correlations, tolerance, and VIF — Figure 2. Coefficients table, second half

However, the collinearity statistics reported in the Coefficients table are unimproved. This is because the z-score transformation does not change the correlation between two variables. As a multicollinearity diagnostic, the condition index is useful for flagging datasets that could cause numerical estimation problems in algorithms that do not internally rescale the independent variables. The z-score transformation solves this problem, but we need another tactic for improving the variance inflation.