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

[James Pustejovsky]

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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