从探索性网络分析转向确认性网络分析:对结构方程建模适应指数和网络心理测量中切断值的评估
Xinkai Du1, Nora Skjerdingstad2, René Freichel3
1Research Institute, Modum Bad Psychiatric Hospital.
Psychological methods
|June 23, 2025
概括
这项研究表明,结构方程建模 (SEM) 合适指数可以用于确认网络分析 (CNA). 为精确的假设测试和检测网络非静止性,建议采用更严格的标准.
科学领域:
- 心理测量 心理测量 心理测量
- 网络分析 网络分析
- 统计建模 统计建模
背景情况:
- 网络模型越来越多地用于现象检测,但经验研究往往是探索性的.
- 结构方程建模 (SEM) 已经建立了适用于网络模型的确认测试方法.
- 在确认网络分析 (CNA) 中,SEM合适指数的表现和适当的标准仍然未被评估.
研究的目的:
- 评估SEM适应指数及其在CNA中的常规切割值的适用性.
- 评估适应指数的性能,用于测试假设的网络结构和评估静止性.
- 为在确认性网络研究中使用SEM适应指数提供实际建议.
主要方法:
- 采用面板图形自回归模型,以对截面和时间序列网络数据进行概括.
- 进行模拟,改变变量 (节点) 的数量,样本大小和测量波.
- 在测试网络结构和静态性时分析了各种SEM合适指数的性能.
主要成果:
- 大多数SEM合适指数在CNA中表现良好.
- I型增量合适指数表现出高的错误拒绝率.
- 传统的SEM切割值在很大程度上可以用于初步CNA评估.
结论:
- SEM适应指数适用于确认网络心理测量,支持理论测试和复制.
- 对于精确的假设测试和复制,建议使用更严格的截止值 (例如,RMSEA ≤ 0.03/0.04,增量合适指数 ≥ 0.96/0.97).
- 建议使用更严格的RMSEA切断来检测网络结构的非静止性.
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