[R-meta] Getting meta-analytic residuals from multilevel models

Dougherty, Liam L|@m@Dougherty @end|ng |rom ||verpoo|@@c@uk
Fri Apr 24 15:13:03 CEST 2020

Dear Wolfgang,

I'm interested in testing for publication bias (e.g. non-publication of small studies) in a meta-analysis dataset with lots of non-independent data points (multiple measurements per study and per species). It seems clear that traditional graphical approaches are not appropriate here. One approach suggested by you (https://stats.stackexchange.com/questions/134768/metafor-package-in-r-ranktest-for-multivariate-meta-analysis) is to run a rma.mv model with study variance as a moderator. This seems to work well and give me a sensible result.

However, if possible I would also like to use the trim-and-fill method, as it gives a nice graphical presentation of the problem. Nakagawa & Santos (2012; doi: 10.1007/s10682-012-9555-5) outline a method for this using meta-analytic residuals, and I�ve come across several papers using this approach, with residuals obtained from the MCMCglmm package (and code available to run this). However I don�t think the predict function in metafor can be used to obtain residuals that take into account the random factors in a multilevel model- it looks to just use the mean estimate.

So my question is: is there any way to obtain meta-analytic residuals from a multilevel model in Metafor? Or do I need to stick to MCMCglmm?

Many thanks,

Liam Dougherty


Dr Liam R. Dougherty

Early Career Research Fellow
Department of Evolution, Ecology and Behaviour
Institute of Integrative Biology
University of Liverpool

Biosciences Building | Room 236
(+44) 0151 795 7771

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