重新评估因子模型的适合性倾向.
Wes Bonifay1, Li Cai2, Carl F Falk3
1University of Missouri.
Psychological methods
|February 10, 2025
概括
本研究检查了拟合倾向 (FP),这是超出参数计数的统计模型复杂性的衡量标准. 它为共同的因素分析模型的FP提供了实用的见解,增强了研究中的模型评估.
科学领域:
- 统计 统计 统计 统计
- 心理测量 心理测量 心理测量
- 量化心理学 量化心理学
背景情况:
- 模型复杂性对于统计模型评估至关重要.
- 拟合倾向 (FP) 量化了模型适应各种数据模式的能力.
- 现有的FP研究是有限的,专注于理论而不是实际应用.
研究的目的:
- 在实践中检查常用的因子分析模型的拟合倾向 (FP).
- 为了为统计模型评估提供历史背景,挑战性参数计数作为唯一的复杂性度量.
- 为未来关于FP在潜变量建模中的研究提供建议.
主要方法:
- 统计模型评估方法的历史审查.
- 使用分析示例对探索性和确认性因子分析模型的分析.
- 与现有关于因素模型FP的说法相关的发现的描述.
主要成果:
- 拟合倾向 (FP) 提供了对模型复杂性的更细致的理解,而不仅仅是参数计数.
- 分析示例说明了广泛使用的探索性和确认性因子分析模型的FP.
- 结果与事实模型FP的先前研究相对应.
结论:
- 在实践中,FP是评估统计模型复杂性的重要指标.
- 建议在潜变量建模中对FP进行进一步的研究.
- 这项研究为评估因素分析模型提供了实际见解.
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