TY - JOUR
T1 - An assessment of statistical methods for nonindependent data in ecological meta-analyses
T2 - Comment
AU - Nakagawa, Shinichi
AU - Senior, Alistair M.
AU - Viechtbauer, Wolfgang
AU - Noble, Daniel W.A.
PY - 2022/1
Y1 - 2022/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85117391717&partnerID=8YFLogxK
U2 - 10.1002/ecy.3490
DO - 10.1002/ecy.3490
M3 - Comment/debate
SN - 0012-9658
VL - 103
JO - Ecology
JF - Ecology
IS - 1
M1 - e03490
ER -