可视化工具包,通过证据地图,文献计量和替代影响指标来丰富元分析
Yefeng Yang1, Malgorzata Lagisz1,2, Shinichi Nakagawa1,2
1Evolution & Ecology Research Centre and School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW, Australia.
Research synthesis methods
|February 2, 2026
概括
这项研究引入了新的数据可视化工具包,以增强元分析. 这些工具整合了定性数据并评估了更广泛的影响,超越了传统的定量方法,以获得更丰富的见解.
科学领域:
- 科学研究方法论科学研究方法论.
- 数据科学是数据科学.
- 信息可视化信息可视化
背景情况:
- 目前的元分析可视化主要侧重于定量数据 (例如,森林地块).
- 对于科学,政策和实践至关重要的定性信息在元分析可视化中经常被忽视.
- 现有的方法缺乏对研究特征,学术影响和社会影响的全面可视化.
研究的目的:
- 引入一个可视化工具包框架,丰富元分析.
- 促进对定量和定性证据的综合.
- 为了能够评估分析证据基础的学术和非学术影响.
主要方法:
- 开发了一个框架,整合了从系统证据映射,文献计量分析和替代影响度量分析的可视化方法.
- 使用开源软件R进行实现,并提供示例可视化.
- 借助大型语言模型 (LLM) 来帮助具有较少R编码经验的用户.
主要成果:
- 引入了用于可视化定性数据,研究特征,知识差距和方法差异的"丰富"工具包.
- 启用对非独立证据 (作者,国家,资金) 的视觉评估,以告知偏见风险.
- 提供了使用替代指标来衡量社会影响和研究翻译的方法.
结论:
- 拟议的可视化工具包通过结合定性数据和影响评估来丰富元分析.
- 这些方法为各种各样的最终用户提供复杂的证据基础的用户友好概要.
- 框架和资源使研究人员能够更全面地想象他们的元分析证据.
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