Notice: On March 31, it was announced that Statalist is moving from an email list to a forum. The old list will shut down on April 23, and its replacement, statalist.org is already up and running.
[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]
Re: st: Fwd: Multicollinearity
Nick Cox <email@example.com>
Re: st: Fwd: Multicollinearity
Tue, 4 Jun 2013 14:42:14 +0100
I would be interested in know of any real systems (physical,
biological, economic, political, social, you get to choose) in which
interesting predictors are expected to be uncorrelated.
On 4 June 2013 15:35, Richard Williams <firstname.lastname@example.org> wrote:
> Paul Allison offers some thoughts on when not to be worried about
> At 10:30 AM 6/3/2013, David Hoaglin wrote:
>> It seems excessive to talk about "multicollinearity" when
>> "collinearity" is already general enough.
>> Whether collinearity is a problem depends on how serious it is and on
>> the particular variables involved. Pairwise correlations may not
>> provide enough information if the collinearity relation involves more
>> than two variables. One can get at the details by using the
>> regression coefficient variance decomposition developed by David
>> Belsley and described in the book by Belsley, Kuh, and Welsch (1980).
>> The implementation in the user-written command -coldiag2- (from SSC,
>> as I recall) is useful.
>> David Hoaglin
>> Belsley D.A., Kuh E., Welsch R.E. (1980). Regression Diagnostics.
>> John Wiley & Sons.
>> On Mon, Jun 3, 2013 at 3:32 AM, Maarten Buis <email@example.com>
>> > --- Prakash Kashwan wrote:
>> >> I am unable to use the stata-listserv, and hence this private
>> >> email to you.
>> > This is probably because you did not sent your message as plain text.
>> > This is explained in the Statalist FAQ
>> > <http://www.stata.com/support/faqs/resources/statalist-faq/#toask>
>> >> I am following up on your response to an old thread about
>> >> multicollinearity
>> >> (http://www.stata.com/statalist/archive/2010-07/msg00675.html).
>> >> I liked your response, which goes against the grain of the
>> >> received wisdom which would have us treat multicollinearity
>> >> as a problem. Have you or someone else published
>> >> something to this effect, which I can cite in a paper?
>> > What is recieved wisdom is very much dependent on which
>> > (sub-(sub-))discipline one belongs to. Here is a fun quote:
>> > "Econometrics texts devote many pages to the problem of
>> > multicollinearity in multiple regression, but they say little about
>> > the closely analogous problem of small sample size in estimation a
>> > univariate mean. Perhaps that imbalance is attributable to the lack of
>> > an exotic polysyllabic name for 'small sample size'. If so, we can
>> > remove that impediment by introducing the term micronumerosity."
>> > Chapter 23.3. of Goldberger, A. S. (1991). A Course in Econometrics.
>> > Harvard University Press, Cambridge MA.
>> > Hope this helps,
>> > Maarten
>> * For searches and help try:
>> * http://www.stata.com/help.cgi?search
>> * http://www.stata.com/support/faqs/resources/statalist-faq/
>> * http://www.ats.ucla.edu/stat/stata/
> Richard Williams, Notre Dame Dept of Sociology
> OFFICE: (574)631-6668, (574)631-6463
> HOME: (574)289-5227
> EMAIL: Richard.A.Williams.5@ND.Edu
> WWW: http://www.nd.edu/~rwilliam
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/faqs/resources/statalist-faq/
> * http://www.ats.ucla.edu/stat/stata/
* For searches and help try: