统计服务于元科学:用可复制率测量复制距离
Erkan O Buzbas1, Berna Devezer1,2
1Department of Mathematics and Statistical Science, University of Idaho, Moscow, ID 83844, USA.
Entropy (Basel, Switzerland)
|October 25, 2024
概括
科学复制性至关重要. 这项研究建议测量研究之间的"复制距离",将可重复性视为一种工具,而不是固有的属性,以改善科学推断并指导未来的研究.
科学领域:
- 统计学哲学 统计学的哲学
- 科学方法科学方法学
- 研究可复制性研究可复制性
背景情况:
- 科学界面临着可重现性危机,影响研究结果的可靠性.
- 目前关于可复制性的讨论往往缺乏评估复制努力的细微框架.
- 了解研究可复制性和结果可复制性之间的关系对于强大的科学推断至关重要.
研究的目的:
- 提出一种用于测量科学研究之间的"复制距离"的新框架.
- 将可重现性重新定义,而不是作为一种内在的品质,而是作为评估复制中偏差的指标.
- 根据科学复制的挑战,提高统计推理的实用性.
主要方法:
- 用于统计推断的科学研究规范的概念分析.
- 开发"复制距离"指标,以量化原始研究与其复制之间的差异.
- 使用玩具示例进行说明性模拟,以展示拟议的框架.
主要成果:
- 最好将可重现性理解为测量与原始研究的距离的工具,而不是固有的可取性质.
- 提出了量化"复制距离"的框架,解决了捕获研究组件的挑战.
- 建议有目的地计划修改,而不是直接复制,因为它对科学研究更有信息.
结论:
- "复制距离"的可量化的测量是必要的,以便对可复制性对科学推理的影响进行可靠的研究.
- 拟议的框架有助于科学家确定"可复制"的研究.
- 基于概率和证据的统计方法被认为是开发更好地为科学实践服务的统计数据的潜在关键.
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