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Re: st: Proportional Independent Variables


From   Nick Cox <njcoxstata@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Proportional Independent Variables
Date   Thu, 28 Feb 2013 08:22:23 +0000

I should have said use 19 at most.

Nick

On Wed, Feb 27, 2013 at 10:12 PM, Nick Cox <njcoxstata@gmail.com> wrote:
> 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?
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