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AW: st: Fixed Effects inconsistency between Correlation and Coefficient Direction


From   "Martin Weiss" <martin.weiss1@gmx.de>
To   <statalist@hsphsun2.harvard.edu>
Subject   AW: st: Fixed Effects inconsistency between Correlation and Coefficient Direction
Date   Mon, 19 Apr 2010 18:41:34 +0200

<> 

Steve, is the single left quote in 

*************
input  id x
 `1     1
*************

intentional? (Omitting it does lead to similar results, though...)


HTH
Martin

-----Ursprüngliche Nachricht-----
Von: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Steve Samuels
Gesendet: Montag, 19. April 2010 18:25
An: statalist@hsphsun2.harvard.edu
Betreff: Re: st: Fixed Effects inconsistency between Correlation and
Coefficient Direction

Here's a data set that qualitatively reproduces the phenomenon you
describe. Note the relatively large between-id variation compared to
within-id variation.  I don't understand your statement about dropping
data.  Please provide a reference.

Steve
**************************CODE BEGINS**************************
clear
input  id x
 `1     1
  1     2
  1     3
  2     4
  2     5
  2     6
  3     7
  3     8
  3     9
end
set seed 123456
gen y = 10*id -x + rnormal(0,1)
xtset id
list
corr y x
xtreg y x, fe
xtreg y x, re
***************************CODE ENDS***************************


On Sun, Apr 18, 2010 at 1:42 PM, MICHAEL ESPOSITO <mespo12@optonline.net>
wrote:
> I have a question that I cannot seem to find an answer to. I am attempting
> to use the fixed effects model for research that I am conducting for my
> dissertation. My committee and I discovered that in certain circumstances
> the results do not seem logical. For instance, the correlation matrix
> indicates a positive relationship between two variables and then when we
run
> the Fixed Effects Linear Regression model using the same two variables,
the
> coefficient indicates a negative relationship.  I suspect that it may be
> related to something I read that stated that the fixed effects model has
the
> tendency to drop a significant amount of data in the independent variable
> when the data is perceived as having a high degree of randomness.
>
> The correlation matrix suggests a positive relationship .2663 and the
> coefficient correlation indicates a negative -1491.  When I run the same
> variables using the linear regression model with the Mixed Effects
> variation, all findings suggest a positive relationship. Does anyone know
> what could be causing this strange occurrence? Any advice or guidance you
> can provide would be most appreciated.


-- 
Steven Samuels
sjsamuels@gmail.com
18 Cantine's Island
Saugerties NY 12477
USA
Voice: 845-246-0774
Fax:    206-202-4783

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