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From | Nick Cox <njcoxstata@gmail.com> |
To | statalist@hsphsun2.harvard.edu |
Subject | Re: st: Proportional Independent Variables |
Date | Wed, 27 Feb 2013 22:12:28 +0000 |
In principle, yes. In practice, the effect might be slight. You could look at e.g. http://www.amazon.co.uk/Compositional-Data-Analysis-Theory-Applications/dp/0470711353/ for ideas on transformations that tackle this issue. My guess is that you will lose more on interpretability than you will gain. But use 19 not 20. Nick On Wed, Feb 27, 2013 at 8:40 PM, nick bungy <nickbungystata@hotmail.co.uk> wrote: > Dear Statalist, > > I have a dependent variable that is continuous > and a set of 20 independent variables that are percentage based, with > the condition that the sum of these variables must be 100% across each > observation. The data is across section only. > > I am aware that > interpretting the coefficients from a general OLS fit will be > inaccurate. The increase of one of the 20 variables will have to be > facilitated by a decrease in one or more of the other 19 variables. > > Is > there an approach to get consistent coefficient estimates of these > parameters that consider the influence of a proportionate decrease in > one or more of the other 20 variables? * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/