在我们信任的模型中:预先注册,大样本和复制可能不够
Martin Spiess1, Pascal Jordan1
1Institute of Psychology, Department of Psychology and Human Movement Science, University of Hamburg, Hamburg, Germany.
Frontiers in psychology
|October 9, 2023
概括
心理学研究中的统计模型必须考虑数据生成过程,特别是关于样本选择和假设有效性的数据. 忽视这些因素,即使采用大量样本或预先注册,也可能导致偏见的结论和有缺陷的推断.
科学领域:
- 心理学研究方法论心理学研究方法论
- 在社会科学中的统计建模.
背景情况:
- 心理学研究中的可复制性是有争议的,但选择机制和统计模型假设往往被忽视.
- 这些被忽视的问题质疑统计工具是否准确地反映了数据生成过程.
研究的目的:
- 调查选择机制和违反模型假设对心理研究中推断的有效性的影响.
- 突出预先注册和大样本等共同策略在解决这些问题的局限性.
主要方法:
- 在选择性抽样条件下分析统计推论有效性.
- 讨论线性模型和通用线性混合模型中违反假设的后果 (例如,在项目响应理论中).
主要成果:
- 从选择性样本的推断仅在非常特定的条件下有效,这与常规做法相反.
- 在心理学研究中,违反模型假设经常被忽视,导致潜在的偏见.
- 标准策略 (预先注册,大样本,复制) 不能解决这些根本问题.
结论:
- 解决选择机制和模型假设对于有效的心理学研究至关重要.
- 模型诊断,选择性补偿方法和非参数估计等策略可以帮助减轻偏差.
- 一个基本的解决方案涉及代理论的发展与统计学上合理的假设和经验研究的自我选择.
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