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AW: st: Fixed Effects inconsistency between Correlation and Coefficient Direction
From
"Martin Weiss" <[email protected]>
To
<[email protected]>
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: [email protected]
[mailto:[email protected]] Im Auftrag von Steve Samuels
Gesendet: Montag, 19. April 2010 18:25
An: [email protected]
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 <[email protected]>
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
[email protected]
18 Cantine's Island
Saugerties NY 12477
USA
Voice: 845-246-0774
Fax: 206-202-4783
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