Advice for improving the reproducibility of data extraction in meta-analysis

Ivimey-Cook, E. R. , Noble, D. W.A., Nakagawa, S., Lajeunesse, M. J. and Pick, J. L. (2023) Advice for improving the reproducibility of data extraction in meta-analysis. Research Synthesis Methods, 14(6), p. 915. (doi: 10.1002/jrsm.1663) (PMID:37571802)

Abstract

Extracting data from studies is the norm in meta-analyses, enabling researchers to generate effect sizes when raw data are otherwise not available. While there has been a general push for increased reproducibility in meta-analysis, the transparency and reproducibility of the data extraction phase is still lagging behind. Unfortunately, there is little guidance of how to make this process more transparent and shareable. To address this, we provide several steps to help increase the reproducibility of data extraction in meta-analysis. We also provide suggestions of R software that can further help with reproducible data policies: the shinyDigitise and juicr packages. Adopting the guiding principles listed here and using the appropriate software will provide a more transparent form of data extraction in meta-analyses.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Ivimey-Cook, Dr Edward

Creator Roles

Ivimey-Cook, E.: Conceptualization, Writing – original draft, Writing – review and editing, Methodology, Data curation, Formal analysis

• Authors: Ivimey-Cook, E. R., Noble, D. W.A., Nakagawa, S., Lajeunesse, M. J., and Pick, J. L.
• College/School: College of Medical Veterinary and Life Sciences > School of Biodiversity, One Health & Veterinary Medicine
• Journal Name: Research Synthesis Methods
• Publisher: Wiley
• ISSN: 1759-2879
• ISSN (Online): 1759-2887
• Published Online: 11 August 2023
• Copyright Holders: Copyright © 2023 The Authors
• First Published: First published in Research Synthesis Methods 14(6):911-915
• Publisher Policy: Reproduced under a Creative Commons license
• Data DOI: 10.5281/zenodo.8187175