This problem is called collinearity or multicollinearity. It is a good idea to find out which variables are nearly collinear with which other variables. The approach in PROC REG follows that of ...

Using three different indicators of the same type—momentum, for example—results in the multiple counting of the same information, a statistical term referred to as multicollinearity.

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Covers simple, multiple, and polynomial regression; estimation, testing, and prediction; weighted least squares, matrix approach, dummy variables, multicollinearity, model diagnostics and variable ...

Predictor variables were first checked for multicollinearity, and the model was tested for overall statistical significance using the Omnibus Test of Model Coefficients. Alpha was set to 0.05 for all ...