4 ms·
Yes. Leaving out likely predictors is worse. Collinearity issues can mean that the beta estimates for collinear variables are less robust, making them harder t
by your-nanny 8y ago
Yes. Leaving out likely predictors is worse.
Collinearity issues can mean that the beta estimates for collinear variables are less robust, making them harder to interpret. Sometimes this is approached by some data reduction technique, eg PCA.