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Rnest:用于因子分析的下一个自身价值足够性测试的R包
1Département des Sciences humaines, Lettres et Communication, Université TÉLUQ, Montréal, Canada.
Multivariate behavioral research
|June 8, 2025
概括
下一个自身价值序列测试 (NEST) 提供了一种可靠的方法来确定探索性因子分析中的因子数. R包Rnest为这种基于统计的技术提供了可访问的软件.
科学领域:
- 心理测量 心理测量 心理测量
- 统计学方法论 统计学方法论
背景情况:
- 在探索性因子分析 (EFA) 中确定正确的因子数量是一个持续的挑战.
- 许多停止规则存在,但没有一个提供了最终的解决方案,导致不一致的应用.
- 与传统方法相比,下一个自身值序列测试 (NEST) 已经证明了理论依据,对交叉负载的稳定性和高精度.
研究的目的:
- 在EFA中引入下一个自身价值序列测试 (NEST) 以保留因子.
- 介绍R套件Rnest,该套件旨在实现NEST.
- 提供使用Rnest的实用工作流程,并提供可重复的示例.
主要方法:
- 该研究引入了下一个自身价值序列测试 (NEST) 作为EFA的新型停止规则.
- 开发的R包Rnest是为了提供NEST的可访问的实现.
- 用一个可重复的数据示例来说明软件包的功能.
主要成果:
- 该Rnest包提供了NEST的实用和可靠的实现.
- NEST表现出强度,低假阳性率,以及对小因素的敏感性.
- 该套件有助于应用理论上有根据且准确的因子保留方法.
结论:
- 该Rnest包解决了对NEST的可访问软件的需求.
- 广泛采用Rnest可以提高探索性因素分析的质量.
- 这个工具支持从业者,心理测量学家和研究人员在做出有关因子保留的明智决策.
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