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


From   Steve Samuels <[email protected]>
To   [email protected]
Subject   Re: st: Fixed Effects inconsistency between Correlation and Coefficient Direction
Date   Mon, 19 Apr 2010 12:54:13 -0400

It was a typo, Martin.

Steve

On Mon, Apr 19, 2010 at 12:41 PM, Martin Weiss <[email protected]> wrote:
>
> <>
>
> 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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