An assessment of statistical methods for non-independent data in ecological meta-analyses: Comment

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1002/ecy.3490. This is version 3 of this Preprint.

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Authors

Shinichi Nakagawa, Alistair M Senior, Wolfgang Viechtbauer, Daniel W.A. Noble

Abstract

Recently, Song et al. (2020) conducted a simulation study using different methods to deal with non-independence resulting from effect sizes originating from the same paper – a common occurrence in ecological meta-analyses. The main methods that were of interest in their simulations were: 1) a standard random-effects model used in combination with a weighted average effect size for each paper (i.e., a two-step method), 2) a standard random-effects model after randomly choosing one effect size per paper, 3) a multilevel (hierarchical) meta-analysis model, modelling paper identity as a random factor, and 4) a meta-analysis making use of a robust variance estimation method. Based on their simulation results, they recommend that meta-analysts should either use the two-step method, which involves taking a weighted paper mean followed by analysis with a random-effects model, or the robust variance estimation method.

DOI

https://doi.org/10.32942/osf.io/w96nv

Subjects

Ecology and Evolutionary Biology, Life Sciences, Other Ecology and Evolutionary Biology

Keywords

Dates

Published: 2021-02-27 19:49

Last Updated: 2023-03-13 23:20

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CC-By Attribution-NonCommercial-NoDerivatives 4.0 International