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R: st: highly skewed, highly zeroed data


From   "Carlo Lazzaro" <carlo.lazzaro@tin.it>
To   <statalist@hsphsun2.harvard.edu>
Subject   R: st: highly skewed, highly zeroed data
Date   Wed, 25 Nov 2009 10:54:02 +0100

Taking Maarten's wise remark forward, Jason (and whoever is interested in
this tricky topic) might want to take a look at "old but gold": 
Manning WG, Mullahy J. Estimating Log Models: To Transform Or Not To
Transform? National Bureau Of Economic Research, Technical Working Paper
246, 1999 (downloadable with some restrictions from
http://www.nber.org/papers/T0246).

Kind Regards,
Carlo

-----Messaggio originale-----
Da: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Maarten buis
Inviato: mercoledì 25 novembre 2009 10.11
A: statalist@hsphsun2.harvard.edu
Oggetto: Re: st: highly skewed, highly zeroed data

--- On Wed, 25/11/09, Jason Ferris wrote:
> I am aware of adding a constant and the transforming on the
> log scale (with antilog) for interpretation.

The previous comments are useful and to the point, all I can
add is that this sugestion by the original poster will _not_ 
give you an estimate of the mean. Notice that the logarithm 
is a non-linear transformation, so taking a logarithm of a 
variable, computing a mean, and than backtransform that mean 
to the original metric will not give you the mean of the 
original variable. If you didn't add the constant you would 
have gotten geometric mean, but by adding the constant you'll 
just get a meaningless number.

Hope this helps,
Maarten

--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany

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


      

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