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From |
Maarten buis <maartenbuis@yahoo.co.uk> |

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

Subject |
Re: st: Modeling % data |

Date |
Wed, 22 Sep 2010 16:19:50 +0000 (GMT) |

--- Austin Nichols wrote: > I don't see how data approaching the boundaries is a problem in > -qreg-, as long as the fraction at the boundary itself is not too > large (though that in itself is more an indictment of the outcome > measure than a necessary problem for quantile regression). If 10% of > the outcomes are at the lower boundary (zero) for low X and 10% of the > outcomes are at the upper boundary (100) for high X, how is that a > problem for estimating how the conditional median changes with X? The problem would be that in those cases is that if X is an continuous variable it is probably not going to have a linear effect. That is what the boundary does. If you are approaching one boundary, than you might get away with adding squares, but if you are approaching both boundaries, like in the case of the original question, things would get much harder (though not impossible). However, in those case I would just go for models in Stata that were written for this type of data like the ones I refered to earlier, rather than try to "fix" -qreg-. Hope this helps, Maarten -------------------------- Maarten L. Buis Institut fuer Soziologie Universitaet Tuebingen Wilhelmstrasse 36 72074 Tuebingen Germany http://www.maartenbuis.nl -------------------------- * * 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/

**Follow-Ups**:**Re: st: Modeling % data***From:*Austin Nichols <austinnichols@gmail.com>

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