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From |
"JVerkuilen (Gmail)" <jvverkuilen@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Can multicollinearity problems be resolved by using residuals from another regression? |

Date |
Sat, 10 Nov 2012 12:16:30 -0500 |

On Thu, Nov 8, 2012 at 9:36 PM, A. Shaul <3c5171@gmail.com> wrote: > Dear Statalist, > > I expect a non-linear effect of an exogenous variable, x1, on a > dependent variable, y. The variable x1 is affected by another > exogenous variable, x2. The variable x2 affects x1 directly and also y > directly. The variable x1 does not affect x2. I am only interested in > the partial effect of x1 on y while controlling for x2 --- or at least > while controlling for the part of the variation in x2 that affects y > directly. > > I have the following regression equation: > > (1) y = b1*x1 + b2*(x1)^2 + b3*x2 + constant I'm not 100% sure what you're doing but when you have polynomial terms like this collinearity is inevitable. Before doing anything odd, center x1 and then compute x1^2, and regress on the centered variables. (You may want to rescale x1 as well but centering does the work.) This will give you a statistically equivalent model that breaks the collinearity between x1 and x1^2. Usually though you're not interpreting x1 terms directly anyhow, so whether x1 or x1^2 is statistically significant individually is irrelevant. Certainly the linear term for x1 is irrelevant if the term for x1^2 is significant. You can test for x1 effects as a block using -testparm-. * * 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/

**Follow-Ups**:**Re: st: Can multicollinearity problems be resolved by using residuals from another regression?***From:*Steve Samuels <sjsamuels@gmail.com>

**References**:**st: Can multicollinearity problems be resolved by using residuals from another regression?***From:*"A. Shaul" <3c5171@gmail.com>

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