在确认因素分析中评估测量模型的模型适合性
David Goretzko1,2, Karik Siemund1, Philipp Sterner1
1Ludwig-Maximilians-Universität München, Germany.
Educational and psychological measurement
|January 22, 2024
概括
在心理学研究中,确认因素分析 (CFA) 模型适合性评估通常是关键的. 许多研究缺乏足够的报告来重新评估,并使用有问题的适合指数切断值.
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:
- 确认因素分析 (CFA) 是开发心理测量模型的一个关键方法.
- 评估CFA模型的合适性是复杂的,因为它需要精确的合适性测试和合适性指数的绝对解释挑战.
- 适合指数的确定的切割规则缺乏普遍适用性和特定环境的定制性.
研究的目的:
- 在心理学研究中审查和批判性地评估CFA中模型合适指数的报告和应用.
- 为了比较报告的适应指数值与已建立的截止规则.
- 用新的方法重新评估模型合适性,采用量身定制的,数据驱动的切断标准.
主要方法:
- 从2015年到2020年发表在"心理评估"上的所有CFA模型的系统审查.
- 报告的适合指数值与现有的截止标准的比较.
- 使用新开发的方法对模型和数据特定的切断值重新评估模型合适性.
主要成果:
- 许多研究显示了可疑的模型匹配,特别是在独立集群约束方面.
- 有相当数量的研究未能报告所有必要的信息,以独立重新评估模型的合适性.
- 与传统的适应指数评估相比,新开发的方法突出显示了差异.
结论:
- 在许多已发表的CFA研究中,对模型适合性的评估需要严格审查.
- 不完整的报告实践阻碍了CFA模型合适性的可靠评估和复制.
- 模型合适性评估的进步需要更新的方法和报告标准.
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