Im working on a linear regression with 3 independent variables (likert scales from 0-6) nothing out of the ordinary.
The IDs correlate from r=.3 to .58 with each other, which is a bit high although the VIF is still under 2. So usually I would assume that the multicollinieraty assumption would be ok here, but I mean-centered to IDs just to see what happens.
After centering, all IDs perfectly correlate with each other, which I dont know if thats an centering artifact or not. Also the VIF is now 1 which seems weird and the regression analysis throws out the 2nd and 3rd ID even when I forced SPSS (method enter) to consider them in the regression.
Any idea what I did wrong here?