This paper has now been accepted for publication in Ecology:
Shinichi Nakagawa, Alistair M. Senior, Wolfgang Viechtbauer, and Daniel W. A. Noble. An assessment of statistical methods for non-independent data in ecological meta-analyses. Ecology, accepted 20 May 2021.
To access the Supplemental Material for implementing corrections click here
This repository houses the code and supplementary tutorial used to demonstrate how multi-level meta-analytic models from metafor can be corrected to avoid infated Type I error in the presence of non-independent effect sizes. The commentary is a response to Song et al. (2020), to show how a few simple corrections can provide some resolution to problems they identify in their very thorough simulations.
Just want to know how to apply corrections? Users who are interested in learning more about how they can correct for non-independence can read the Supplemental Material
Reproducing the simulations? Users wanting to reproduce Song et al's (2020) simulations, along with the correlations implemented by us can find all the R code in tge R/ directory.
Song, C., S. D. Peacor, C. W. Osenberg, and J. R. Bence. 2020. An assessment of statistical methods for nonindependent data in ecological meta-analyses. Ecology online: e03184.