thank you all for you help,
i will try to center the variables.
frank
On 8/17/07, Roger Harbord <[email protected]> wrote:
> -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
> >
> >
>
>
>
> *
> * For searches and help try:
> * http://www.stata.com/support/faqs/res/findit.html
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
