In Regression model, collinearity means that within the set of predictor variables, some of the predictor variables are (nearly) totally predicted by the other independent variables . When the predictor variables are highly correlated amongst themselves, the coefficients of the resulting least squares fit may be very imprecise. By allowing a small amount of bias in the estimates, more reasonable coefficients may often be obtained. Ridge regression is one method to address these issues. Often, small amounts of bias lead to dramatic reductions in the variance of the estimated model coefficients. In SPSS, you can use the following syntax to perform Ridge regression.
INCLUDE 』C:\Program Files\SPSS\Ridge regression.sps'.
RIDGEREG DEP=Y /ENTER = X1 to Xp
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