在数据中通过欧米茄系数高估内部一致性,从而产生中心点类因子解决方案
Karl Schweizer1, Tengfei Wang2, Xuezhu Ren3
1Goethe University Frankfurt, Germany.
Educational and psychological measurement
|February 17, 2025
概括
欧米茄系数是衡量内部一致性的指标,在特定的因素分析场景中可能会被高估. 这发生在小型数据集中的异质模式中,影响可靠性估计.
科学领域:
- 心理测量 心理测量 心理测量
- 统计建模 统计建模
背景情况:
- 欧米茄系数是评估心理测量研究内部一致性的关键指标.
- 确认因素分析 (CFA) 被广泛用于评估测量模型.
- 以变量为中心的因子解决方案可以为可靠性估计带来独特的挑战.
研究的目的:
- 在以变量为重点的因子解决方案中研究欧米茄系数的偏差.
- 了解相关性模式如何影响欧米茄估计.
- 为了确定Omega可能不准确的条件.
主要方法:
- 在确认因素分析中对相关性模式的分析.
- 在以变量为焦点的溶液中检查因子负载.
- 一个模拟研究来评估Omega系数的性能.
主要成果:
- 异质的相关性模式可能导致Omega估计的膨胀.
- 偏差在数据集中更明显,数据集中明显变量较少.
- 不同质性的程度直接影响偏差的大小.
结论:
- 在解释Omega系数时,需要仔细考虑以变量为中心的因子解决方案.
- 提出了一种方法来识别这些解决方案并管理欧米茄偏差.
- 准确的可靠性估计需要了解底层的相关结构.
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