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st: AW: RE: AW: questions about panel data analysis and outliers.


From   "Martin Weiss" <martin.weiss1@gmx.de>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: AW: RE: AW: questions about panel data analysis and outliers.
Date   Mon, 17 May 2010 13:51:31 +0200

<> 

" True, although it's not hard to find outliers on a bivariate
distribution which aren't outliers on either marginal."


The "double negation" is baffling me. Is it hard or not to find them?




HTH
Martin


-----Ursprüngliche Nachricht-----
Von: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Nick Cox
Gesendet: Montag, 17. Mai 2010 13:42
An: statalist@hsphsun2.harvard.edu
Betreff: st: RE: AW: questions about panel data analysis and outliers.

True, although it's not hard to find outliers on a bivariate
distribution which aren't outliers on either marginal. 

Other answers include 

1. Omit the putative outlier and see how much difference it makes.

2. Decide you should be using a transformation or non-identity link
function. 

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

Martin Weiss

" My second question is: how can I estimate correlation without
outliers?"

You can qualify on the candidate variables not being outliers based on
their
univariate distribution, if that is what you mean:


*************
sysuse auto, clear
qui su mpg,d
gen byte within=inrange(mpg, r(p5), r(p95))
qui su weight,d
gen byte within2=inrange(weight, r(p5), r(p95))
corr mpg weight if within & within2
corr mpg weight
*************

Amatoallah ouchen
I have a panel data (T=3 and N=45) and  I want to perform a robust
regression, so I would like to know if it is ok if I cope with this
just as a simple  cross sectional  analysis (because the number of my
time serie is so thin).
what do you think about that?
My second question is: how can I estimate correlation without outliers?


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