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From |
Kit Baum <[email protected]> |

To |
[email protected] |

Subject |
st: Re: confidence intervals on r-squared |

Date |
Tue, 16 Oct 2007 06:09:36 -0400 |

Marcello indicates that one can indeed provide confidence intervals for the r^2 statistic. My point is that as one can arbitrarily increase r^2 by tossing anything lying around (e.g. interactions, polynomial terms, anything not completely random) into the regression, you can with probability 1 place r^2=1 in such a confidence interval. But what does that mean? I agree with Nick. "Improving your model" is not a matter of maximizing r^2 (we all know how to do that without any reference to the underlying discipline- specific theory). The model should be a tradeoff between explanatory power and parsimony, and r^2 is not made for that objective. Adjusted r^2, although imperfect, at least penalizes the inclusion of lots of junk.

Kit Baum, Boston College Economics and DIW Berlin

http://ideas.repec.org/e/pba1.html

An Introduction to Modern Econometrics Using Stata:

http://www.stata-press.com/books/imeus.html

On Oct 16, 2007, at 2:33 AM, statalist-digest wrote:

Oblique answer: You can do this, but it is better to devote the surplus energy you would spend on it thinking about the interpretation of your model, whether you can improve it, and so forth. Nick [email protected] Marcello PaganoCorrect answer: R-squared is a statistic around which you can set a confidence interval. It is just somewhat complicated to give the general formula, although it is available in particular cases. Which case are you interested in?

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**Follow-Ups**:**Re: st: Re: confidence intervals on r-squared***From:*Marcello Pagano <[email protected]>

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