[R-meta] imputing covariance matrices for meta-analysis of dependent effects
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 [[alternative HTML version deleted]]
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