6.11 Collinearity

Collinearity (see Section 5.20) is a characteristic of the predictors, not the outcome, and so can be a problem not only in linear regression, but also in all other types of regression models. For logistic regression, diagnose collinearity in the same way as for MLR, using VIFs or aGSIFs.

Example 6.3 (continued): Evaluate collinearity in the adjusted model without an interaction. The aGSIFs are all small, so we conclude there is no problem with collinearity.

car::vif(fit.ex6.3.adj)

##                 GVIF Df GVIF^(1/(2*Df))
## alc_agefirst   1.044  1           1.022
## demog_age_cat6 1.094  4           1.011
## demog_sex      1.038  1           1.019
## demog_income   1.086  3           1.014