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From |
Austin Nichols <austinnichols@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Modeling % data |

Date |
Thu, 23 Sep 2010 14:12:53 -0400 |

Maarten-- -qreg- requires no "fix" using higher powers of X in the general case. I referred the original poster to -glm- as well, in http://www.stata.com/statalist/archive/2010-09/msg00981.html but your objection to -qreg- is unfounded in the case I outlined--if X is a continuous variable (did you mean unbounded, maybe?) there is no reason it cannot have a linear effect on the conditional median of y, even if y is bounded between 0 and 1, and even if there is a nonzero fraction at the boundaries. Of course, if a significant fraction of the data piles up at the boundary, neither -qreg- nor -glm- will be a particularly good model, and the typical researcher may prefer a MLE that has a two-part flavor to it (requiring some strong assumptions about the distribution of errors). On Wed, Sep 22, 2010 at 12:19 PM, Maarten buis <maartenbuis@yahoo.co.uk> wrote: > --- 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-. * * 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:*Nick Cox <n.j.cox@durham.ac.uk>

**References**:**Re: st: Modeling % data***From:*Maarten buis <maartenbuis@yahoo.co.uk>

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