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元分析软件应用中的挑战与担忧:探索科学综合的领域

Challenges and Concerns in the Utilization of Meta-Analysis Software: Navigating the Landscape of Scientific Synthesis.

作者信息

Yadav Sankalp

机构信息

Medicine, Shri Madan Lal Khurana Chest Clinic, New Delhi, IND.

出版信息

Cureus. 2024 Jan 31;16(1):e53322. doi: 10.7759/cureus.53322. eCollection 2024 Jan.

DOI:10.7759/cureus.53322
PMID:38435898
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10906933/
Abstract

Meta-analysis has emerged as a pivotal tool for synthesizing evidence in scientific research, facilitated by the advent of meta-analysis software. While these tools have significantly streamlined the synthesis process, challenges and concerns persist, impacting the reliability and validity of meta-analytic findings. This editorial addresses key issues in the use of meta-analysis software, including heterogeneity, publication bias, data quality, model dependence, and user competence. As the scientific community increasingly relies on meta-analytic approaches, collaborative efforts are needed to establish standardized reporting guidelines, enhance data quality, and improve transparency. This study highlights the importance of addressing these challenges to ensure the continued evolution of meta-analysis as a robust and informative method for evidence synthesis in scientific research.

摘要

随着元分析软件的出现,元分析已成为科学研究中综合证据的关键工具。虽然这些工具显著简化了综合过程,但挑战和问题依然存在,影响着元分析结果的可靠性和有效性。这篇社论讨论了使用元分析软件的关键问题,包括异质性、发表偏倚、数据质量、模型依赖性和用户能力。随着科学界越来越依赖元分析方法,需要共同努力制定标准化的报告指南,提高数据质量,并增强透明度。本研究强调应对这些挑战的重要性,以确保元分析作为科学研究中一种强大且信息丰富的证据综合方法持续发展。

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本文引用的文献

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BMC Med. 2023 Mar 29;21(1):112. doi: 10.1186/s12916-023-02823-9.
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Meta-analysis. What have we learned?荟萃分析。我们学到了什么?
Injury. 2023 May;54 Suppl 3:S30-S34. doi: 10.1016/j.injury.2022.06.012. Epub 2022 Jun 12.
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A systematic comparison of software dedicated to meta-analysis of causal studies.因果研究的荟萃分析专用软件的系统比较。
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