Advice for Improving the Reproducibility of Data Extraction in Meta-Analysis
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| Title: | Advice for Improving the Reproducibility of Data Extraction in Meta-Analysis |
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| Language: | English |
| Authors: | Ivimey-Cook, Edward R. (ORCID |
| Source: | Research Synthesis Methods. 2023 14(6):911-915. |
| Availability: | Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us |
| Peer Reviewed: | Y |
| Page Count: | 5 |
| Publication Date: | 2023 |
| Document Type: | Journal Articles Reports - Descriptive |
| Descriptors: | Replication (Evaluation), Data Collection, Meta Analysis, Computer Software, Statistical Analysis |
| DOI: | 10.1002/jrsm.1663 |
| ISSN: | 1759-2879 1759-2887 |
| 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. |
| Abstractor: | As Provided |
| Notes: | https://doi.org/10.5281/zenodo.8187175 |
| Entry Date: | 2023 |
| Accession Number: | EJ1399239 |
| Database: | ERIC |
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