Re: st: Variance decomposition

["Michael Crain" <michaelcrain@hotmail.com>]

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 <maartenbuis@yahoo.co.uk>
Subject: Re: st: Variance decomposition
Date: Sun, 11 Mar 2007 13:59:08 +0000 (GMT)

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--- Michael Crain <michaelcrain@hotmail.com> 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
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+31 20 5986715

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