Multicollinearity is a common problem when estimating linear or generalized linear models, including logistic regression and Cox regression. It occurs when there are high correlations among predictor variables, leading to unreliable and unstable estimates of regression coefficients. Most data analysts know that multicollinearity is not a good thing.  But many do not realize that there … Continue reading When Can You Safely Ignore Multicollinearity?