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2. Enriching meta-analyses through scoping review, bibliometrics, and alternative impact metrics: Visualizing study characteristics, hidden risk of bias, societal influence, and research translation

Author

Yang, Yefeng, Lagisz, Malgorzata, and Nakagawa, Shinichi

Subjects
Computer Science - Digital Libraries, Statistics - Applications
Abstract

We present a framework consisting of three approaches that can enhance meta-analyses: 1) scoping reviews (evidence map), 2) bibliometrics, and 3) alternative impact metrics. These three "enrichment" approaches facilitate the research synthesis of both quantitative and qualitative evidence, along with academic and non-academic influences. While the meta-analysis yields quantitative insights (e.g., overall estimates), the enrichment analyses provide user-friendly summaries of qualitative information on the evidence base. Scoping reviews can visualize study characteristics, unravelling knowledge gaps and methodological differences. Bibliometric analysis offers a visual assessment of the non-independent evidence, such as hyper-dominant authors and countries, and funding sources, potentially informing the risk of bias. Impact metric analysis employs alternative metrics to gauge societal influence and research translation (e.g., policy and patent citations) of studies in the meta-analysis. To illustrate the application of this framework, we provide sample visualizations and R code.

Published
2023

10. Method Reporting with Initials for Transparency (MeRIT) promotes more granularity and accountability for author contributions

Author

Nakagawa, Shinichi, Ivimey-Cook, Edward R., Grainger, Matthew J., O’Dea, Rose E., Burke, Samantha, Drobniak, Szymon M., Gould, Elliot, Macartney, Erin L., Martinig, April Robin, Morrison, Kyle, Paquet, Matthieu, Pick, Joel L., Pottier, Patrice, Ricolfi, Lorenzo, Wilkinson, David P., Willcox, Aaron, Williams, Coralie, Wilson, Laura A. B., Windecker, Saras M., Yang, Yefeng, and Lagisz, Malgorzata

Published
2023
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27. Transparent reporting items for simulation studies evaluating statistical methods: Foundations for reproducibility and reliability.

Author

Williams, Coralie, Yang, Yefeng, Lagisz, Malgorzata, Morrison, Kyle, Ricolfi, Lorenzo, Warton, David I., and Nakagawa, Shinichi

Subjects
MONTE Carlo method, OPEN scholarship, EVALUATION methodology, RESEARCH methodology
Abstract

Copyright of Methods in Ecology & Evolution is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2024
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30. "Best Paper" awards lack transparency, inclusivity, and support for Open Science.

Author

Lagisz, Malgorzata, Rutkowska, Joanna, Aich, Upama, Ross, Robert M., Santana, Manuela S., Wang, Joshua, Trubanová, Nina, Page, Matthew J., Pua, Andrew Adrian Yu, Yang, Yefeng, Amin, Bawan, Martinig, April Robin, Barnett, Adrian, Surendran, Aswathi, Zhang, Ju, Borg, David N., Elisee, Jafsia, Wrightson, James G., and Nakagawa, Shinichi

Subjects
OPEN scholarship, AWARDS, SCIENCE awards, RESEARCH awards, EDUCATORS
Abstract

Awards can propel academic careers. They also reflect the culture and values of the scientific community. But do awards incentivize greater transparency, inclusivity, and openness in science? Our cross-disciplinary survey of 222 awards for the "best" journal articles across all 27 SCImago subject areas revealed that journals and learned societies administering such awards generally publish little detail on their procedures and criteria. Award descriptions were brief, rarely including contact details or information on the nominations pool. Nominations of underrepresented groups were not explicitly encouraged, and concepts that align with Open Science were almost absent from the assessment criteria. At the same time, 10% of awards, especially the recently established ones, tended to use article-level impact metrics. USA-affiliated researchers dominated the winner's pool (48%), while researchers from the Global South were uncommon (11%). Sixty-one percent of individual winners were men. Overall, Best Paper awards miss the global calls for greater transparency and equitable access to academic recognition. We provide concrete and implementable recommendations for scientific awards to improve the scientific recognition system and incentives for better scientific practice. Research awards are an integral part of the universal "prestige economy" in science, but do they incentivize greater transparency, inclusivity, and openness? This study uses cross-disciplinary data to explore the level of transparency of publicly available award descriptions and assessment criteria, asking whether such awards contribute to or propagate existing reproducibility crises and inequities in science. [ABSTRACT FROM AUTHOR]

Published
2024
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41. Meta-analysis of variation in sport and exercise science: examples of application within resistance training research

Author

Steele, James, Fisher, James P, Smith, Dave, Schoenfeld, Brad J, Yang, Yefeng, Nakagawa, Shinichi, Steele, James, Fisher, James P, Smith, Dave, Schoenfeld, Brad J, Yang, Yefeng, and Nakagawa, Shinichi

Abstract

Meta-analysis has become commonplace within sport and exercise science for synthesising and summarising empirical studies. However, most research in the field focuses upon mean effects, particularly the effects of interventions to improve outcomes such as fitness or performance. It is thought that individual responses to interventions vary considerably. Hence, interest has increased in exploring precision or personalised exercise approaches. Not only is the mean often affected by interventions, but variation may also be impacted. Exploration of variation in studies such as randomised controlled trials (RCTs) can yield insight into interindividual heterogeneity in response to interventions and help determine generalisability of effects. Yet, larger samples sizes than those used for typical mean effects are required when probing variation. Thus, in a field with small samples such as sport and exercise science, exploration of variation through a meta-analytic framework is appealing. Despite the value of embracing and exploring variation alongside mean effects in sport and exercise science, it is rarely applied to research synthesis through meta-analysis. We introduce and evaluate different effect size calculations along with models for meta-analysis of variation using relatable examples from resistance training RCTs.

Published
2023

47. Construction of Small FeS2 Nanoparticles Embedded in Porous Nitrogen-Doped Carbon with Enhanced Sodium Ion Storage Properties.

Author

Wen, Yi, Sun, Qianqian, Gao, Jinyi, Hu, Jiajia, Yao, Zhujun, Liu, Tiancun, Shen, Shenghui, and Yang, Yefeng

Subjects
DOPING agents (Chemistry), ELECTRIC conductivity, COMPOSITE materials, DIFFUSION kinetics, ELECTRIC batteries, SUPERCAPACITOR electrodes, SODIUM ions
Abstract

Iron disulfide (FeS2) is a potentially suitable anode material for sodium-ion batteries (SIBs) by virtue of its high theoretical capacity (894 mAh g−1). Unfortunately, the inferior electrical conductivity, sluggish diffusion kinetics, and large volume changes have impeded its practical application. Here, we report a composite material comprising numerous small FeS2 nanoparticles intimately embedded in a porous N-doped carbon framework through high-energy ball milling combined with stepwise post-thermal treatment. The highly porous and robust external carbon framework serves as a conductive substrate and has good strain accommodation for small FeS2 nanoparticles, which can not only boost electron/ion transport ability of the composite but also provide extra active sites for sodium ion storage and maintain the structural integrity of the composite during repeated cycling processes. As a result, the FeS2/PNC electrode achieves high initial Coulombic efficiency of 81%, reversible specific capacities of 530 mA h g−1 with good capacity retentions of 95% after 200 cycles at 1 A g−1 , and a superior rate capability (376 mA h g−1 at 5 A g−1). The promising electrochemical performance and the facile synthesis method make the FeS2/PNC composite a potential candidate material as a SIBs anode for large-scale preparation and application in the future. [ABSTRACT FROM AUTHOR]

Published
2023
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50. Low statistical power and overestimated anthropogenic impacts, exacerbated by publication bias, dominate field studies in global change biology

Author

Yang, Yefeng, Hillebrand, Helmut, Lagisz, Malgorzata, Cleasby, Ian, Nakagawa, Shinichi, Yang, Yefeng, Hillebrand, Helmut, Lagisz, Malgorzata, Cleasby, Ian, and Nakagawa, Shinichi

Abstract

Field studies are essential to reliably quantify ecological responses to global change because they are exposed to realistic climate manipulations. Yet such studies are limited in replicates, resulting in less power and, therefore, potentially unreliable effect estimates. Furthermore, while manipulative field experiments are assumed to be more powerful than non-manipulative observations, it has rarely been scrutinized using extensive data. Here, using 3847 field experiments that were designed to estimate the effect of environmental stressors on ecosystems, we systematically quantified their statistical power and magnitude (Type M) and sign (Type S) errors. Our investigations focused upon the reliability of field experiments to assess the effect of stressors on both ecosystem's response magnitude and variability. When controlling for publication bias, single experiments were underpowered to detect response magnitude (median power: 18%–38% depending on effect sizes). Single experiments also had much lower power to detect response variability (6%–12% depending on effect sizes) than response magnitude. Such underpowered studies could exaggerate estimates of response magnitude by 2–3 times (Type M errors) and variability by 4–10 times. Type S errors were comparatively rare. These observations indicate that low power, coupled with publication bias, inflates the estimates of anthropogenic impacts. Importantly, we found that meta-analyses largely mitigated the issues of low power and exaggerated effect size estimates. Rather surprisingly, manipulative experiments and non-manipulative observations had very similar results in terms of their power, Type M and S errors. Therefore, the previous assumption about the superiority of manipulative experiments in terms of power is overstated. These results call for highly powered field studies to reliably inform theory building and policymaking, via more collaboration and team science, and large-scale ecosystem facilities. Future stud

Published
2022

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