preprints_ui: apdxk_v2
Data license: ODbL (database) & original licenses (content) · Data source: Open Science Framework
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| apdxk_v2 | A scoping review on metrics to quantify reproducibility: a multitude of questions leads to a multitude of metrics | *Background:* Reproducibility is recognized as essential to scientific progress and integrity. Replication studies and large-scale replication projects, aiming to quantify different aspects of reproducibility, have become more common. Since no standardized approach to measuring reproducibility exists,a diverse set of metrics has emerged and a comprehensive overview is needed. *Methods:* We conducted a scoping review to identify large-scale replication projects that used metrics and methodological papers that proposed or discussed metrics. The project list was compiled by the authors. For the methodological papers, we searched Scopus, MedLine, PsycINFO andEconLit. Records were screened in duplicate against predefined inclusion criteria. Demographic information on included records and information on reproducibility metrics used, suggested or discussed was extracted. *Results:* We identified 49 large-scale projects and 97 methodological papers, and extracted 50 metrics. The metrics were characterized based on type (formulas and/or statistical models, frameworks, graphical representations, studies and questionnaires, algorithms), input required, and appropriate application scenarios. Each metric addresses a distinct question. *Conclusions:* Our review provides a comprehensive resource in the form of a “live”, interactive table for future replication teams and meta-researchers, offering support in how to select the most appropriate metrics that are aligned with research questions and project goals. | 2025-04-10T17:05:37.769602 | 2025-04-10T23:00:14.148319 | 2025-04-10T23:00:14.114745 | metaarxiv | 1 | accepted | 2 | 1 | https://doi.org/10.31222/osf.io/apdxk_v2 | CC-By Attribution 4.0 International | Generalizability; Literature Review; Meta-research; Metrics; Quantify; Replicability; Reproducibility; Translatability | ["Generalizability", "Literature Review", "Meta-research", "Metrics", "Quantify", "Replicability", "Reproducibility", "Translatability"] | Rachel Heyard; Samuel Pawel; Joris Frese; Bernhard Voelkl; Hanno Würbel; Sarah McCann; Leonhard Held; Kimberley Wever; Helena Hartmann; Louise Townsin | [{"id": "yd85p", "name": "Rachel Heyard", "index": 0, "orcid": "0000-0002-7531-4333", "bibliographic": true}, {"id": "pvs62", "name": "Samuel Pawel", "index": 1, "orcid": "0000-0003-2779-320X", "bibliographic": true}, {"id": "wrv62", "name": "Joris Frese", "index": 2, "orcid": "0000-0002-5871-997X", "bibliographic": true}, {"id": "t4gy7", "name": "Bernhard Voelkl", "index": 3, "orcid": null, "bibliographic": true}, {"id": "fnw5d", "name": "Hanno W\u00fcrbel", "index": 4, "orcid": "0000-0002-2934-3010", "bibliographic": true}, {"id": "qcxz4", "name": "Sarah McCann", "index": 5, "orcid": "0000-0003-4737-2349", "bibliographic": true}, {"id": "g7634", "name": "Leonhard Held", "index": 6, "orcid": "0000-0002-8686-5325", "bibliographic": true}, {"id": "du2pj", "name": "Kimberley Wever", "index": 7, "orcid": "0000-0003-3635-3660", "bibliographic": true}, {"id": "457pk", "name": "Helena Hartmann", "index": 8, "orcid": "0000-0002-1331-6683", "bibliographic": true}, {"id": "2xzre", "name": "Louise Townsin", "index": 9, "orcid": "0000-0002-2212-1626", "bibliographic": true}] | Rachel Heyard | Social and Behavioral Sciences; Library and Information Science; Social Statistics; Medicine and Health Sciences; Other Medicine and Health Sciences; Scholarly Communication; Physical Sciences and Mathematics; Statistics and Probability; Statistical Methodology | [{"id": "5c81de83e48c52001647c154", "text": "Social and Behavioral Sciences"}, {"id": "5c81de83e48c52001647c159", "text": "Library and Information Science"}, {"id": "5c81de84e48c52001647c15d", "text": "Social Statistics"}, {"id": "5c81de84e48c52001647c160", "text": "Medicine and Health Sciences"}, {"id": "5c81de84e48c52001647c165", "text": "Other Medicine and Health Sciences"}, {"id": "5c81de84e48c52001647c16a", "text": "Scholarly Communication"}, {"id": "5c81de84e48c52001647c176", "text": "Physical Sciences and Mathematics"}, {"id": "5c81de85e48c52001647c180", "text": "Statistics and Probability"}, {"id": "5c81de85e48c52001647c18f", "text": "Statistical Methodology"}] | https://osf.io/download/67f7faada279ca40da8b8124 | 1 | SP and LH have developed two of the metrics identified in this review. RH, BV, HW, SKM, LH, KW and SZ receive funding from iRISE. iRISE receives funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101094853. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Executive Agency (ERA). Neither the European Union nor the ERA can be held responsible for them. iRISE also receives funding from the Swiss State Secretariat for Education, Research and Innovation (SERI): Direct Funding for Collaborative Projects as part of the transitional measures, and from UK Research and Innovation (UKRI). HH was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation - Project-ID 422744262 -TRR 289). | available | available | ["https://osf.io/j65wb"] | 2025-04-11T00:11:49.570448 |