小样本,大见解:对于潜伏的分歧思维模型的估计技术的方法比较
Selina Weiss1, Lara S Elmdust1, Benjamin Goecke2
1Institute of Psychology, University of Hildesheim, Universitätsplatz 1, 31141 Hildesheim, Germany.
Journal of Intelligence
|November 26, 2025
概括
贝叶斯结构方程建模 (SEM) 为心理学中小样本大小的频率主义方法提供了强大的替代方案. 这项研究证明了贝叶斯式的SEM.
科学领域:
- 心理学 心理学 心理学
- 量化心理学 量化心理学
- 心理测量 心理测量 心理测量
背景情况:
- 样本规模较小在心理学研究中构成重大挑战,特别是对于专家群体或复杂的方法论.
- 频率主义确认因子分析 (CFA) 对样本大小敏感,导致趋同问题,不可接受的参数和模型不合适.
- 贝叶斯方法提供了一个强大的替代方案,受样本大小的影响较小,并且能够结合先前的知识.
研究的目的:
- 为创造力研究引入小样本结构方程建模 (SEM).
- 通过使用有限样本大小的SEM,研究创意流,创意聪明和右翼威权主义 (RWA) 之间的关系.
- 在逐渐小的样本大小下,比较频率主义者与贝叶斯式SEM的稳定性和可靠性.
主要方法:
- 使用结构方程建模 (SEM),比较频率主义和贝叶斯主义方法.
- 该研究以N = 198的样本大小开始,并逐渐减少n = 25.
- 评估的关键指标包括频率合适指数和贝叶斯式Rhat值,以及标准误差和回归系数.
主要成果:
- 在N = 100的样本大小以下,频率适应指数显著降低.
- 贝叶斯多变量Rhat值表明稳定收到N = 50.
- 与贝叶斯估计相比,在频率主义的SEM中,流动性负载的标准误差膨胀速度比贝叶斯估计快40-50%,而RWA-cleverness回归系数在所有样本减少中仍然显著.
结论:
- 贝叶斯先验在稳定小样本大小的SEM结果方面发挥着至关重要的作用.
- 右翼专制主义和创造性聪明之间的关系即使在有限的样本规模中也表现出强度.
- 这些发现为心理学研究中的双因素建模中确定最小样本大小提供了实际指导方针.
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