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RE: st: RE: Multicollinerity test in IV regression
Excellent advice. I did say "often", not always.
> -----Original Message-----
> From: firstname.lastname@example.org
> [mailto:email@example.com]On Behalf Of Marcello
> Sent: 13 October 2004 22:34
> To: firstname.lastname@example.org
> Subject: Re: st: RE: Multicollinerity test in IV regression
> I agree somewhat with what Nick says, but I would like to take
> it one step further. Indeed, mathematically one can think of the
> predictors, over this particular sample region, as defining a linear
> space. If the space is not of full rank, then there is
> That means that a linear combination of two, or more of the
> predictor variables, or even linear combinations of two or more of
> the predictor variables, equal zero.
> In the finite precision world we live in with computers, zero is
> interpreted to be relatively small. This is especially important
> in the statistical world we live in where the predictors themselves
> (big secret) may be known with error.
> These linear combinations are not unique, but, and here is where
> I disagree with Nick, they are informative. Possibly because it is
> not clear that the solution is the simple one implied by Nick:
> drop one, or more, variables until we get rid of the problem.
> A better solution might be to replace all offending predictors
> by (a) linear combination(s) that make sense. For example if
> X1+X2=0, then drop both X1 and X2 and replace them with the
> new variable X1+X2. You can extend this to the more general
> Just a thought.
> Nick Cox wrote:
> >I assert that multicollinearity is a property of the
> >predictors and does not depend on what
> >you do with them before, during or
> >after any examination of multicollinearity.
> >You can look at the structure of relationships
> >with -graph matrix-; get numerical summaries
> >by using -correlate-; and use -_rmcoll- to
> >look further.
> >Whether there is some omnibus test of multicollinearity
> >I do not know. If there were, it wouldn't necessarily
> >be helpful in indicating what to do.
> >I have always found it most useful
> >to think about the meanings of variables and the
> >roles they play in terms of the underlying science.
> >That is, reflection often makes it seem unsurprising
> >that two or more variables are highly correlated,
> >so that they tell the same story and only one
> >need be recorded.
> >However, there are other issues particularly where
> >lots of dummies are included.
> >Rozilee Asid
> >>Just to ask one simple question, how do I test for the existence of
> >>multicollinearity after using ivreg2 command.
> >* 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/
> Marcello Pagano
> Biostatistics Department Tel: 1-617-432-4911
> Harvard School of Public Health Fax:
> 655 Huntington Avenue
> Boston, MA 02115
eppur si muove
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