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From |
"Martin Weiss" <martin.weiss1@gmx.de> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: Re: Detecting collinearity during regression analysis |

Date |
Tue, 10 Feb 2009 20:43:27 +0100 |

<>

********* clear* set obs 10000 *correlated covariates corr2data x1 x2, corr(1, .1\ .1, 1) cstorage(full) g y=1+2*x1+3*x2+rnormal() reg y x1 x2 *small vifs estat vif *DGP with correlated covariates clear* set obs 10000 corr2data x1 x2, corr(1, .999\ .999, 1) cstorage(full) g y=1+2*x1+3*x2+rnormal() reg y x1 x2 *see the massive vifs estat vif ********** HTH Martin _______________________

To: <statalist@hsphsun2.harvard.edu> Sent: Tuesday, February 10, 2009 8:28 PM Subject: st: Detecting collinearity during regression analysis

Hello and thank you in advance, I have a question about detecting collinearity. First, see my example: ***BEGIN*** sysuse auto, clear xi: qreg mpg foreign i.make, nolog ***END***Note in this example that I used quantile regression to determine effectsof foreign and make on MPG.I used xi command to create dummy categorical variables for make (notethat this creates quite a large number of variables for make, as make is acontinuous variable, but I did this for example).Note that the coefficients are very small (e.g. e^-15), approaching zero. In this example, does this indicate collinearity? And why?The reason I used such a granular dummy categorization for make is tohighlight my example. In my real data, I have age and wage. When I usecategories such as age/10 or wage/10000, this gives me "collinearity"(i.e. very small coefficients). When I collapse these age or wagecategories to smaller categories (i.e. age or wage as binomial variables,greater than or less than a certain value), I correct this problem of"collinearity".Am I correct in my assumptions? Thank you. _________________________________________________________________ Windows Live Messenger. Multitasking at its finest. http://www.microsoft.com/windows/windowslive/products/messenger.aspx * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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**References**:**st: Detecting collinearity during regression analysis***From:*Anon Mouse <anon556656@live.ca>

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