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循证视角下的偏倚识别:基于Egger拓展模型的大数据元分析 被引量:1

Bias Identification from an Evidence-Based Perspective:A Big Data Meta-Analysis Procedure Based on Eggers Extension Model
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摘要 证据综合是实现学术研究发现向实践指南制定转化的桥梁,元分析作为证据整合与转化工具,是循证体系建设的核心。然而,由于偏倚的存在,元分析结果的可靠性难以保障。针对循证研究过程中普遍存在的选择偏移和结果报告偏倚,本研究旨在围绕Egger等发展的模型,通过元回归对其加以拓展,并通过数学分解的方法对选择偏移和结果报告偏倚加以有效识别,从而发展出一种用于识别偏倚的新方法。在建立了精确的偏倚识别拓展模型的基础上,本研究使用一组经验研究数据,验证了拓展模型的合理性与科学性。本研究提出的拓展模型有效提高了Egger检验的效率,有助于提升元分析质量、构建和完善科学化的循证社会科学基础理论体系。 Research synthesis serves as a bridge between academic research findings and the development of practice guidelines.As a tool for evidence integration and translation,meta-analysis is at the core of evidence-based practice.However,the reliability of meta-analysis results is often compromised by biases.Addressing the common issues of selection bias and outcome reporting bias in the process of evidence synthesis,this study aims to extend the model developed by Egger and others through meta-regression.It employs a mathematical decomposition method to effectively identify selection bias and outcome reporting bias,thus developing a new approach for bias identification.Building upon the establishment of an accurate bias identification extension model,this study further validates the rationality and scientific validity of the extended model using a set of empirical research data. The developed extension model significantly enhances the efficien‐cy of Egger’s test, contributes to improving the quality of meta-analysis, and aids in the construction and refinement of a scientific evidence-based social science theoretical framework.
作者 周文杰 林伟杰 魏志鹏 杨克虎 Zhou Wenjie;Lin Weijie;Wei Zhipeng;Yang Kehu(School of Information Resource Management,Renmin University of China,Beijing 100080;Business School of Northwest Normal University,Lanzhou 730070;School of Economics and Management,Beijing Jiaotong University,Beijing 100044;Evidence-Based Medical Center of School of Basic Medical Sciences of Lanzhou University,Lanzhou 730030;Cross-Innovation Laboratory of Evidence-Based Social Science of Lanzhou University,Lanzhou 730030)
出处 《情报学报》 CSSCI CSCD 北大核心 2024年第4期491-502,共12页 Journal of the China Society for Scientific and Technical Information
基金 国家社会科学基金重大项目“循证社会科学的理论体系、国际经验与中国路径研究”(19ZDA142)。
关键词 偏倚识别 Egger拓展模型 元分析 证据综合 bias identification Egger extension model meta-analysis research synthesis
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