Accessibility navigation


A robust and readily implementable method for the meta-analysis of response ratios with and without missing standard deviations

Nakagawa, S., Noble, D. W. A., Lagisz, M., Spake, R. ORCID: https://orcid.org/0000-0003-4671-2225, Viechtbauer, W. and Senior, A. M. (2023) A robust and readily implementable method for the meta-analysis of response ratios with and without missing standard deviations. Ecology Letters, 26 (2). pp. 232-244. ISSN 1461-0248

[img]
Preview
Text (Open Access) - Published Version
· Available under License Creative Commons Attribution.
· Please see our End User Agreement before downloading.

58MB
[img] Text - Accepted Version
· Restricted to Repository staff only

2MB

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1111/ele.14144

Abstract/Summary

The log response ratio, lnRR, is the most frequently used effect size statistic for meta-analysis in ecology. However, often missing standard deviations (SDs) prevent estimation of the sampling variance of lnRR. We propose new methods to deal with missing SDs via a weighted average coefficient of variation (CV) estimated from studies in the dataset that do report SDs. Across a suite of simulated conditions, we find that using the average CV to estimate sampling variances for all observations, regardless of missingness, performs with minimal bias. Surprisingly, even with missing SDs, this simple method outperforms the conventional approach (basing each effect size on its individual study-specific CV) with complete data. This is because the conventional method ultimately yields less precise estimates of the sampling variances than using the pooled CV from multiple studies. Our approach is broadly applicable and can be implemented in all meta-analyses of lnRR, regardless of ‘missingness’.

Item Type:Article
Refereed:Yes
Divisions:Life Sciences > School of Biological Sciences > Ecology and Evolutionary Biology
ID Code:109391
Publisher:Wiley

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation