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st: RE: RE: Dependent variable is a proportion


From   "Nick Cox" <n.j.cox@durham.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: RE: Dependent variable is a proportion
Date   Thu, 13 May 2004 12:11:57 +0100

This looks like a valuable reference. From the abstract, 
which is in the public domain, I note recommendation 
of (among others) beta-distribution-based models for which -betafit- 
on SSC may be of some use. 

Note, however, the subtle but crucial notation point that 
observations are on (0,1). The problem
which started this thread (see bottom) has observations
on [0,1). i.e. some values are 0. Does the 
paper address this complication to anyone's knowledge? 

Nick 
n.j.cox@durham.ac.uk 

Moran, John
 
> A good review of this problem (the authors used various 
> packages, including
> Stata 7) is given in: R. Kieschnick and B. D. McCullough. Regression
> analysis of variates observed on (0,1): percentages, proportions and
> fractions. Statistical modelling 3:193-213, 2003.

TELHAJ Shqiponje 
 
> The dependent variable I have is a proportion (percentage of 16 year
> olds enrolled in a particular subject) which is between 0 and 86
> percent. I am not sure about the linear form. My dependent 
> variable is 0
> only in 3,980 cases out of 112,412 sample obs. Here a zero is a
> structural one, because the school does not offer history (which is
> choice subject). 
> 
> Would somebody suggest to me whether it would be better to perform a
> logit transformation, or estimate -glm- with family(gaussian) and
> link(logit). Any suggestion would be greatly appreciated!

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