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st: Re: multicollinearity


From   "Martin Weiss" <martin.weiss1@gmx.de>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: Re: multicollinearity
Date   Wed, 19 Nov 2008 21:13:13 +0100

Line for the server...

http://www.stata.com/support/faqs/stat/anova.html

It is easy enough to induce Stata to drop...

************
sysuse auto, clear
reg pr we f
g domestic=!f
reg pr we f dome
************

HTH
Martin
_______________________
----- Original Message ----- From: "Chris Witte" <eljefespeaks@yahoo.com>
To: <statalist@hsphsun2.harvard.edu>
Sent: Wednesday, November 19, 2008 9:06 PM
Subject: st: multicollinearity


Is there another way to get the following module (the link isn't working for me)?

Example . Stata learning module on regression diagnostics: Multicollinearity
. . . . . . . . . . . . . . . . . . UCLA Academic Technology Services
12/03 http://www.ats.ucla.edu/stat/stata/modules/reg/multico.htm


Also, I have read that -anova- and -regress- will drop variables that have collinearity problems, but I have never had Stata drop variables on me. For example:

sysuse auto
reg price headroom trunk weight length turn displacement gear_ratio

Source | SS df MS Number of obs = 74
-------------+------------------------------ F( 7, 66) = 8.18
Model | 295089440 7 42155634.3 Prob > F = 0.0000
Residual | 339975956 66 5151150.85 R-squared = 0.4647
-------------+------------------------------ Adj R-squared = 0.4079
Total | 635065396 73 8699525.97 Root MSE = 2269.6
------------------------------------------------------------------------------
price | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
headroom | -788.1489 423.1895 -1.86 0.067 -1633.074 56.77608
trunk | 109.2235 103.9332 1.05 0.297 -98.28582 316.7328
weight | 5.300069 1.331056 3.98 0.000 2.642531 7.957607
length | -73.59571 42.42778 -1.73 0.087 -158.3055 11.11408
turn | -301.2525 124.9576 -2.41 0.019 -550.7384 -51.76669
displacement | 11.4282 7.622549 1.50 0.139 -3.790711 26.64711
gear_ratio | 2236.615 1051.394 2.13 0.037 137.4391 4335.791
_cons | 7795.908 6103.469 1.28 0.206 -4390.061 19981.88
------------------------------------------------------------------------------


and the correlation between weight and length is 0.9460. Why aren't one of these variables dropped? Does there have to be perfect correlation for dropping variables?





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