[R-meta] imputing covariance matrices for meta-analysis of dependent effects

[Michael Dewey]

Dear James

Not sure how relevant this is but does it complement in any way the 
package  https://CRAN.R-project.org/package=metavcov ? I have not used 
it by the way.

Michael

On 10/08/2017 15:04, James Pustejovsky wrote:
> All,
>
> A common problem in multivariate meta-analysis is that the information
> needed to calculate the correlation between effect size estimates is not
> reported in available sources, even when the variances of the estimates can
> be calculated. One approach to handling this situation is to simply make an
> informed guess about the correlation between the effect sizes. I use this
> approach fairly often and have written a function that makes some of the
> calculations easier. The function calculates a block-diagonal
> variance-covariance matrix based on the sampling variances and a guess
> about the degree of correlation. More details available here:
>
> http://jepusto.github.io/imputing-covariance-matrices-for-multi-variate-meta-analysis
>
> There's nothing innovative about the methods I describe, but I figured that
> others might find the function useful. I would welcome comments, questions,
> or debate about the utility of the approach I used.
>
> Cheers,
> James
>
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>
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-- 
Michael
http://www.dewey.myzen.co.uk/home.html