基于图形理论的相似度指标可以比较亚人口心理测量网络
Esther Ulitzsch1, Saurabh Khanna2, Mijke Rhemtulla3
1Leibniz Institute for Science and Mathematics Education (IPN).
Psychological methods
|December 21, 2023
概括
研究人员为心理测量网络开发了一种新的相似度衡,以量化群体之间的差异. 这种网络分析工具补充了现有的网络不变性测试,有助于理解心理变量关系.
科学领域:
- 心理测量 心理测量 心理测量
- 网络分析 网络分析
- 图形理论 图形理论
背景情况:
- 网络心理测量使用马尔科夫随机场来以图形形式建模心理变量依赖关系.
- 通过对各个子群体的心理测量网络进行比较至关重要,因为最近在不变性测试方面取得了进展.
- 缺乏对心理测量网络差异影响大小的定量衡量方法.
研究的目的:
- 引入一种直观的相似度计,用于量化心理测量网络之间的差异程度.
- 为了补充现有的网络不变性的统计测试.
主要方法:
- 提出了一种基于Frobenius规范在加权相邻矩阵中差异的新型相似度衡.
- 通过检查其与隐性变量和高斯图形模型中的网络差异的关系来评估该措施的实用性.
- 进行了模拟研究,以评估有限样本行为.
主要成果:
- 拟议的措施直观地捕捉了各种网络差异,优于传统的基于相关性的比较.
- 该措施为具有足够样本规模的不同网络提供可靠的结果.
- 当人口网络相同时,测量可能无法检测到确切的相似性.
结论:
- 新的相似度测量是心理测量网络不变性的统计测试的宝贵补充.
- 它提供了一种定量方法,以了解跨群体网络差异的程度.
- 推与网络相似性的显著性测试一起使用.
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