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From |
Richard Herrell <rherre2@uic.edu> |

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

Subject |
Re: st: RE: proportion as a dependent variable |

Date |
Mon, 14 Jul 2003 15:41:22 -0500 (CDT) |

How would one model, say, hematocrit as a DV (% of red blood cells in whole blood) in a way that the predictor variables would have a clear biological interpretation? On Mon, 14 Jul 2003, Nick Cox wrote: > Ronnie Babigumira > > > I was attending a workshop in which one of the presenters > > had a regression > > in which a dependent variable was a proportion. One of the > > participants > > noted that it was wrong but didnt follow it up with a clear > > explanation. > > Presumably the argument was that, given predictor x, > a linear form a + bx must predict response values outside [0,1] for > some x, so that at least in principle the functional > form cannot be appropriate. In practice, if response were (say) > proportion female and x were time, then the time at which the > proportion passed outside the interval might be far outside the > range of the data, but there are plenty of exceptions. > > This is most commonly mentioned, at least in my reading, > as a simple argument why a + bx is likely to be a poor form > for predicting responses which are either 0 or 1, an > argument which usually leads to a case for logit or > probit models. But the argument seems almost as strong > for proportions. And -- historically -- logit as a > transformation for continuous responses preceded logit > as (in modern terms) a link function for binary responses. > (The terminology of logit is more recent than its use.) > > Generalised linear models offer a nice approach to this > question using e.g. logit link and some sensible family. > > There is a FAQ with further comments at > > How does one estimate a model when the dependent variable > is a proportion? > http://www.stata.com/support/faqs/stat/logit.html > > Nick > n.j.cox@durham.ac.uk > > * > * For searches and help try: > * http://www.stata.com/support/faqs/res/findit.html > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: RE: proportion as a dependent variable***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

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