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Re: st: Variance decomposition
This methodolgy is different from ANOVA.
Under a variance components approach, the variance of each of the factors is
independently generated by a random process. Once the variance of a factor
has been estimated, it remains fixed for the remainder of the analysis. The
variance components approach uses zero means and constant but unknown
variances for all the factors. (Only the error term meets this criteria
under ANOVA.) Therefore, each factor can be disentangled from the other
factors to explain each one independent of the others. The substance of
this approach is to explain that the differences among the factor variances
are natural and independent of the other effects. The ultimate result of
this analysis is expressed as a measure of relative importance of each
factor. ANOVA allows us to test statistical significance but does not allow
one to find relative importance.
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From: Maarten buis <[email protected]>
Subject: Re: st: Variance decomposition
Date: Sun, 11 Mar 2007 13:59:08 +0000 (GMT)
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--- Michael Crain <[email protected]> wrote:
I am trying to determine whether any Stata programs are available for
variance decomposition.
<snip>
The framework explains the overall variance in rates of return by
decomposing it into the sum of the variances of various factors plus an
error term.
Isn't that just an ANOVA?
-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting address:
Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
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