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MLR and Collinearity

Collinear variables are a major problem with MLR modeling. Two variables are said to be collinear if they are approximately (or exactly) linearly dependent, or in other words, if there is a high correlation between the two variables. If a model is based on highly correlated variables, the estimated regression coefficients become unstable. This renders the coefficients useless for causal interpretation.

There are at least three ways to determine collinearity:
 


Last Update: 2006-Jšn-17