[R-meta] Getting meta-analytic residuals from multilevel models
L|@m@Dougherty @end|ng |rom ||verpoo|@@c@uk
Fri Apr 24 15:13:03 CEST 2020
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?
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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