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Re: st: Interpretation of Variace Estimates (xtmixed)


From   John Antonakis <john.antonakis@unil.ch>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Interpretation of Variace Estimates (xtmixed)
Date   Wed, 02 Sep 2009 17:42:47 +0200

Hi:

Take a look at pages 102-103.

Best,
J.

____________________________________________________

Prof. John Antonakis
Associate Dean Faculty of Business and Economics
University of Lausanne
Internef #618
CH-1015 Lausanne-Dorigny
Switzerland

Tel ++41 (0)21 692-3438
Fax ++41 (0)21 692-3305

Faculty page:
http://www.hec.unil.ch/people/jantonakis&cl=en

Personal page:
http://www.hec.unil.ch/jantonakis
____________________________________________________



On 02.09.2009 17:21, Christian Weiß wrote:
Dear John,

browsing to my edition of this book I could not find the respective
topic (R-square in multilevel models). Could you provide any more
detailed reference to the book?

Viele Grüße
Christian




On Tue, Sep 1, 2009 at 6:13 AM, John Antonakis<john.antonakis@unil.ch> wrote:
Hi:

There should also be formulas for r-square, at level 1 and 2 are in:

Rabe-Hesketh, S., & Skrondal, A. (2008). Multilevel and Longitudinal
Modeling Using Stata. College Station, TX: Stata Press.

Best,
J.

____________________________________________________

Prof. John Antonakis
Associate Dean Faculty of Business and Economics
University of Lausanne
Internef #618
CH-1015 Lausanne-Dorigny
Switzerland

Tel ++41 (0)21 692-3438
Fax ++41 (0)21 692-3305

Faculty page:
http://www.hec.unil.ch/people/jantonakis&cl=en

Personal page:
http://www.hec.unil.ch/jantonakis
____________________________________________________



On 01.09.2009 11:11, Maarten buis wrote:
--- On Mon, 31/8/09, Christian Weiß wrote:
Please assume xtmixed ,variance yields the following
result.


---------------------------------------------------------------------------
Random-effects Parameters | Estimate Std. Err. [95% Conf.
Interval]

-----------------------------+---------------------------------------------
Variable1: Identity |
var(_cons) | 100.000 70.000 54.22297 415.9787

-----------------------------+---------------------------------------------
Variable2: Identity |
var(_cons) | 10.0000 6.000 4.254477 36.79754

-----------------------------+---------------------------------------------
var(Residual) | 400.000 40.000 397.8473 465.2598

---------------------------------------------------------------------------

Is it 'correct' to conclude that this estimated model
yields a total variance of 510 (100+10+400) and
accordingly variable1 explains about 20% and variable
2% of the total model or is that a total
misinterpretation?
I once knew the answer, now I only know the reference:
chapter 7 of Tom Snijders and Roel Bosker (1999)
"Multilevel Analysis, An introduction to basic and
advanced multilevel modeling". Thousand Oaks: Sage.

Hope this is still of some help,
Maarten

-----------------------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany

http://home.fsw.vu.nl/m.buis/
-----------------------------------------





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