Reliability of meta-analyses in ecology and evolution: (mostly) good news from a case study on sexual signals

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Authors

Pietro Pollo, Malgorzata Lagisz , Renato Chaves Macedo-Rego, Ayumi Mizuno , Yefeng Yang, Shinichi Nakagawa

Abstract

Meta-analyses are powerful synthesis tools that are popular in ecology and evolution due to the rapidly growing literature of this field. Although the usefulness of meta-analyses depends on their reliability, such as the precision of individual and mean effect sizes, attempts to reproduce meta-analyses’ results remain rare in ecology and evolution. Here, we assess the reliability of 41 meta-analyses on sexual signals by evaluating the reproducibility and replicability of their results. We attempted to (1) reproduce meta-analyses’ mean effect sizes using the datasets they provided, (2) reproduce meta-analyses’ effect sizes by re-extracting 5,703 effect sizes from 246 empirical studies they used as sources, (3) assess the extent of relevant data missed by original meta-analyses, and (4) replicate meta-analyses’ mean effect sizes after incorporating re-extracted and relevant missing data. We found many discrepancies between meta-analyses’ reported results and those generated by our analyses for all reproducibility and replicability attempts. Nonetheless, we argue that the meta-analyses we evaluated are largely reproducible and replicable because the differences we found were small in magnitude, leaving the original interpretation of these meta-analyses’ results unchanged. Still, we highlight issues we observed in these meta-analyses that affected their reliability, providing recommendations to ameliorate them.

DOI

https://doi.org/10.32942/X2MW6F

Subjects

Behavior and Ethology, Ecology and Evolutionary Biology, Evolution

Keywords

Dates

Published: 2024-11-09 00:45

Last Updated: 2024-11-20 13:27

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License

CC-By Attribution-NonCommercial-NoDerivatives 4.0 International

Additional Metadata

Language:
English

Conflict of interest statement:
We declare no competing interests.

Data and Code Availability Statement:
All data and code used in this study are available at: https://osf.io/6njem/?view_only=7b01538fb32e4f78b7130b6e8f303649.