在元分析结构方程建模中处理依赖效果大小的六种方法:有没有黄金标准?
Zeynep Şiir Bilici1, Wim Van den Noortgate2,3, Suzanne Jak1
1University of Amsterdam, Amsterdam, The Netherlands.
Research synthesis methods
|February 2, 2026
概括
当前的元分析结构方程建模 (MASEM) 方法在单个研究中的多个效果大小方面扎. 这项模拟研究比较了各种策略,发现没有一种方法在所有标准中脱而出,强调了需要改进技术的需要.
科学领域:
- 心理测量 心理测量 心理测量
- 统计建模 统计建模
- 进行元分析分析.
背景情况:
- 超分析结构方程建模 (MASEM) 面临的挑战是研究中的依赖效果大小.
- 当前的方法,如独立性假设,随机选择或平均效果大小,可能会导致偏见的估计或失去了统计能力.
研究的目的:
- 在MASEM中比较处理依赖效果大小的不同策略的性能.
- 通过模拟对现有方法进行评估,包括单变量三级建模在内的策略.
主要方法:
- 进行了一项模拟研究,以比较MASEM中处理依赖效应大小的各种策略.
- 条件变化包括研究数量,依赖效果大小的数量,效果大小之间的相关性,路径系数大小和研究间的差异.
主要成果:
- 在所有评估标准 (偏见,标准错误,信任区间覆盖率,效率,功率) 中,没有一个单一策略始终优于其他策略.
- 每个策略的表现取决于特定的模拟条件,特别是效果大小之间的依赖程度.
结论:
- 在MASEM中处理依赖效果大小的现有方法是不理想的.
- 显然需要开发和验证更强大的统计技术,以解决元分析中的依赖效应大小.
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