分析和比较单变量,多变量和双因素通用性理论设计层次结构的人格特征的设计
Walter P Vispoel1, Hyeryung Lee1, Tingting Chen1
1University of Iowa, Iowa City, IA, USA.
Journal of personality assessment
|November 8, 2023
概括
结构方程模型增强了对人格评估的概括性理论分析,比如五大库存 (BFI-2). 多变量和双因素模型提供优越的概括性指数和子尺度评估,改善得分可靠性的洞察力.
科学领域:
- 心理测量 心理测量 心理测量
- 人格心理学 人格心理学
- 量化心理学 量化心理学
背景情况:
- 一般化理论 (G理论) 对于评估得分可靠性至关重要.
- 结构方程建模 (SEM) 为复杂的G理论设计提供了灵活的框架.
- 大五大库存 (BFI-2) 提供了强大的个性衡量标准,包括多方面的子域.
研究的目的:
- 展示基于G理论的单变量,多变量和双因素模型的SEM应用.
- 使用这些SEM设计,分析多次BFI-2数据的概括性.
- 评估不同的G理论模型对理解个性评分可靠性的有用性.
主要方法:
- 利用结构方程模型 (SEM) 来实现G理论设计.
- 从扩展的五大库存 (BFI-2) 中分析了多次数据.
- 在SEM中采用单变量,多变量和双因素建模方法.
主要成果:
- SEM有效地代表了G理论对人格评估的设计.
- 多变量和双因素模型为复合分数提供了更好的概括性指数.
- 双因素模型使得得分数差异的详细分区和子尺度贡献的评估.
结论:
- 对项目和场合效应的核算对于准确的概括性至关重要.
- 多变量和双因素SEM设计为人格评分可靠性和维度提供了先进的见解.
- 该研究提供了实施这些先进的G理论分析的实际指导方针和R代码.
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