使用结构化组预测和推理可复制性
Bonnie C Wintle1, Eden T Smith2, Martin Bush2
1MetaMelb Research Initiative, School of Ecosystem and Forest Sciences, University of Melbourne, Parkville 3010, Australia.
Royal Society open science
|June 9, 2023
概括
专家使用IDEA协议准确地预测了研究可复制性. 更广泛的推理,考虑诸如效应大小和声誉等因素,改善了社会和行为科学中的预测准确性.
科学领域:
- 社会和行为科学 社会和行为科学
- 研究方法研究方法论.
- 科学判断 科学判断
背景情况:
- 评估研究的可复制性对于科学进步至关重要.
- 关于可复制性的判断可以受到各种认知和上下文因素的影响.
研究的目的:
- 探索专家如何判断研究可复制性.
- 为了确定驱动准确可复制性判断的因素.
主要方法:
- 使用IDEA协议 (调查,讨论,估计,汇总) 的混合方法方法.
- 雇佣了五个专家小组来评估25个研究声明与复制数据.
- 收集有关参与者的判断和推理的定性和定量数据.
主要成果:
- 参与者在预测研究可复制性方面取得了84%的准确性.
- 更广泛的推理和考虑诸如"效果大小"和"声誉"等因素与更高的准确性相关.
- 有证据表明,统计素养与可重复性判断的准确性之间存在联系.
结论:
- 专家的判断可以在预测研究可复制性方面非常准确.
- 鼓励各种推理策略和统计素养可以提高科学评估的可靠性.
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