[R-sig-eco] Weighting coefficient of variation (CV) in meta-analysis

[Chris Howden]

To some extent your capturing sampling effort in the SD.

maybe weight by the se of the mean?

But overall why weight? If each CV is a single estimate why is one any
more important than another? Once you answer that question than you
will know how to weight.

But be careful weighting, you will increase the variance of your
estimates. So unless u need to don't.

Weighting effectively reduces your sample size  To understand how much
u can calculate the effective sample size which u can the compare to
your actual sample size. (and which u should also use in our your
statistical calculations that require sample size.


What ever weighting

Chris Howden
Founding Partner
Tricky Solutions
Tricky Solutions 4 Tricky Problems
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chris at trickysolutions.com.au

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On 11/11/2011, at 4:48, Scott Chamberlain <scttchamberlain4 at gmail.com> wrote:

> All,
>
> I am doing a meta-analysis where our response variable is CV of effect
> sizes (e.g., CV = sd/mean, where sd and mean are calculated from multiple
> effect sizes from the same study).
>
> Does anyone know the appropriate way to weight CV?  We want to weight CV to
> account for different sampling effort and uncertainty in the CV among
> studies.  We can use standard deviation/variance of CV, but that
> calculation includes CV in it(!!), so that larger CVs have smaller
> variances, and vice versa (at least in our dataset).  What about weighting
> CV by 1/sample size instead?
>
> Thanks for any guidance!
> __
> Scott Chamberlain
> Rice University, EEB Dept.
>
>    [[alternative HTML version deleted]]
>
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