对于纵向和双向数据的动态测量不变度截止值
1Department of Psychology, Arizona State University, PO Box 871104, Tempe, AZ, 85287, USA. dmcneish@asu.edu.
Behavior research methods
|March 14, 2026
概括
动态测量不变度 (DMI) 为行为研究提供了量身定制的切断值. 这项研究将DMI扩展到依赖组 (DG-DMI),为纵向和双向数据分析提供了新的指导.
科学领域:
- 心理测量 心理测量 心理测量
- 行为科学 行为科学
- 统计建模 统计建模
背景情况:
- 测量不变性确保了跨组或跨时间的得分可比性.
- 传统的适合指数切断具有有限的概括性.
- 动态测量不变性 (DMI) 提供定制的切割值,但仅限于独立组.
研究的目的:
- 将动态测量不变度 (DMI) 切割值扩展到依赖组 (DG-DMI).
- 为解释在模型中的适合指数差异提供指导,这些模型具有跨组相关的响应.
- 为了解决对纵向和双向数据的当前方法的局限性.
主要方法:
- 建议和描述 DG-DMI 方法.
- 使用对依赖群体的统计建模,与群体之间的相关性.
- 将GD-DMI应用于三个实证示例.
主要成果:
- 展示DG-DMI用于评估依赖组中的测量不变性的应用.
- 提供经验证据证明DG-DMI在纵向和二次数据中的实用性.
- 为实际实施提供开源软件.
结论:
- 总局-DMI将DMI原则扩展到依赖组,增强测量不变性分析.
- 拟议的方法为研究人员提供了重要的指导,研究人员使用纵向或双向数据.
- 在复杂的数据结构中,DG-DMI促进了对复杂数据结构中得分可比性的更准确和更可概括的结论.
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