# Re: st: Variance decomposition

 From "Michael Crain" To statalist@hsphsun2.harvard.edu Subject Re: st: Variance decomposition Date Sun, 11 Mar 2007 12:41:30 -0500

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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The Netherlands

Buitenveldertselaan 3 (Metropolitan), room Z434

+31 20 5986715

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