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RE: st: Beta values in QREG


From   "Scott Holupka" <scott.holupka@jhu.edu>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Beta values in QREG
Date   Mon, 24 Jun 2013 09:36:41 -0400

Thanks.  I didn't want to ask for coding help until I was sure it was really
a coding problem and not a more fundamental problem with the approach.  So
you're first comment answers my more general question.  If I'm understanding
it correctly, your point is why I would want to standardize values using a
measure of central tendency if I already believe my measures are not
normally-distributed, which, after all, is the reason for using
quantile/median regression.  

Scott



-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Maarten Buis
Sent: Saturday, June 22, 2013 3:34 PM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: Beta values in QREG

On Fri, Jun 21, 2013 at 10:03 PM, Scott Holupka wrote:
> Does anyone know if there is a statistical reason why the Stata 
> quantile regression program "qreg" does not provide an option for 
> producing beta values?  I know a question about beta values in qreg 
> was raised just a few months ago, and the one response suggested that 
> there might be a statistical reason why the option wasn't available, 
> but I didn't see anything more definitive.

The logic behind quantile regression is all about avoiding the first (and
second) moments and replacing those by the more robust quantiles.
So substantively it would not make much sense to bring those moments back in
a quantile regression by standardizing your variables. If you thought that
your data was so problematic that you needed the more robust quantile
regression, then it would be weird to use the non-robust standard deviation
to define the scale of your variable. It is technically possible, but I
would not recommend it.

> I did try standardizing all of my variables and re-running QREG, as 
> had been previously suggested, but the results between the 
> unstandardized and standardized models seem so different I'm not sure 
> if I did something wrong or if there's a more fundamental reason why the
results don't line up.

In order for us to be able to judge that we would need to see what you have
done. We cannot spot errors in code you don't show us.

-- Maarten

---------------------------------
Maarten L. Buis
WZB
Reichpietschufer 50
10785 Berlin
Germany

http://www.maartenbuis.nl
---------------------------------
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