The more overlap among the independent variables in a multiple correlation analysis, the greater the sum of each variable's unique amount of shared variance with the dependent variable.

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In multiple correlation analysis, the more overlap among the independent variables (multicollinearity), the less unique variance each variable contributes to the dependent variable, as shared variance is counted multiple times.

The More Overlap Among the Independent Variables in a Multiple