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Re: st: Re: random effects panel model - interpretation of rho=0


From   "Martin Weiss" <martin.weiss1@gmx.de>
To   <statalist@hsphsun2.harvard.edu>
Subject   Re: st: Re: random effects panel model - interpretation of rho=0
Date   Wed, 20 May 2009 22:25:34 +0200

<>

Very ture and my fault, conditioning on e(sample) only means the rows/observations used in estimation are summarized. To restrict to the covariates/columns, install Maarten`s -ssc d indeplist- and then, post-estimation:

***
indeplist
xtsum `r(X)' if e(sample)
***


HTH
Martin
_______________________
----- Original Message ----- From: "P K" <statistics_2009@yahoo.de>
To: <statalist@hsphsun2.harvard.edu>
Sent: Wednesday, May 20, 2009 10:20 PM
Subject: AW: st: Re: random effects panel model - interpretation of rho=0


Hi Martin,

it gives me the summary of most variables in my dataset, which are far more than the ones used in the regression. Can I limit the command somehow to the variables used in my estimation? ...otherwise I would have to create a separate dataset for the variables used in the regression...

thanks



----- Ursprüngliche Mail ----
Von: Martin Weiss <martin.weiss1@gmx.de>
An: statalist@hsphsun2.harvard.edu
Gesendet: Mittwoch, den 20. Mai 2009, 14:01:43 Uhr
Betreff: st: Re: random effects panel model - interpretation of rho=0

<>

What does -xtsum if e(sample)- after estimation give you?


HTH
Martin
_______________________
----- Original Message ----- From: "P K" <statistics_2009@yahoo.de>
To: <statalist@hsphsun2.harvard.edu>
Sent: Wednesday, May 20, 2009 7:52 PM
Subject: st: random effects panel model - interpretation of rho=0



Hi,

I run a random effects panel model of 64 subjects for 10 years each and have a question concerning the results: My output tells me that 0% of the variance of the dependent variable is between subjects and 100% is within subjects (rho).

I am not sure whether I understand the interpretation correctly, but I find this result a bit uncommon given that I test for a random effects model and
my theory predicts a lot of variation between my subjects.

Could there by any mistake in the analysis?
Thanks,
Pat

Here's the STATA output:

Random-effects GLS regression                   Number of obs      = 545
Group variable: number                          Number of groups   = 64

R-sq:  within  = 0.0138                         Obs per group: min = 2
      between = 0.1741                                        avg = 8.5
      overall = 0.0168                                        max = 10

Random effects u_i ~ Gaussian                   Wald chi2(7)       = 9.16
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.2416

------------------------------------------------------------------------------
AverCh~2adj2 | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
duration_c~e | -.9013214 .3550697 -2.54 011 -1.597245 -.2053976 sicchange | 2.527742 4.073774 0.62 0.535 -5.456709 10.51219 ukdum | .5491039 1.126746 0.49 0.626 -1.659277 2.757485 frendum | -1.780095 1.522111 -1.17 0.242 -4.763378 1.203189 regnlistdum | -.6389011 1.09439 -0.58 0.559 -2.783865 1.506063
     mutdum |   .9720512   1.790017     0.54   0.587    -2.536318 4.48042
lgcount_st~y | -.2016355 .6181168 -0.33 0.744 -1.413122 1.009851 _cons | 1.249498 1.361879 0.92 0.359 -1.419735 3.918731
-------------+----------------------------------------------------------------
    sigma_u |          0
    sigma_e |  11.774903
        rho |          0   (fraction of variance due to u_i)
------------------------------------------------------------------------------




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