-coldiag2- doesn't check for correlation, it checks for collinearity. A
constant doesn't vary so its covariance with any variable is zero and
the correlation isn't defined.
If you found high collinearity between an independent variable and the
constant that would imply that the variable's mean is large compared to
its variance. I'm not sure that would necessarily be a problem, but you
could consider centering it or otherwise changing its origin to be
closer to its mean if you want to reduce the collinearity.
frank palme wrote:
> hello list,
>
> i have a simple question which is bothering me. i could not find any
> answer to it in the literature.
>
> i used the coldiag2 command to check for correlation. i found high
> correlation between an independent variable and the constant. but the
> theoretical part of my thesis clearly suggests to include a constant.
>
> does anybody know what to do to get around that problem?
>
> thank you very much
>
> frank
>
>
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