估计和测试调解效应的信号噪声比:结构方程建模与使用加权复合材料进行路径分析
Ke-Hai Yuan1,2, Zhiyong Zhang2, Lijuan Wang2
1Renmin University of China.
Psychometrika
|February 25, 2026
概括
与结构方程建模 (SEM) 相比,使用加权复合材料 (PAWC) 的路径分析为调解分析提供了更高的准确性和精度. PAWC显示了更高的信号噪声比率,特别是在测量误差的情况下,使其在统计学上更有效和更强大.
科学领域:
- 社会和行为科学 社会和行为科学
- 统计建模 统计建模
背景情况:
- 调解分析对于理解因果关系过程至关重要.
- 之前对SEM和PAWC进行调解分析的比较可能由于潜在变量扩展问题而缺乏有效性.
- 测量错误可能会导致复合分数中的参数估计偏差.
研究的目的:
- 在调解分析中,将结构方程建模 (SEM) 和路径分析与加权复合材料 (PAWC) 的准确性和精度进行比较.
- 为参数估计引入信号噪声比 (SNR) 作为独立于隐性变量尺度的指标.
- 评估PAWC与SEM的统计效率和能力.
主要方法:
- 使用信号与噪声比率 (SNR) 进行参数估计的SEM和PAWC的比较.
- 在调解分析中对间接影响估计的分析.
- 调查影响SEMSNR和PAWC性能的条件.
主要成果:
- 在调解分析中,PAWC总是比SEM产生更高的SNR,即使测量错误.
- 通过因子得分的路径分析表明SNR比SEM高得多.
- 与同等加权复合材料 (EWC) 的调解分析也显示了较高的SNR与SEM相比.
- 在强大的预测器-调解器关系下,PAWC的优势更为明显,但调解器的预测错误可能会对PAWC产生负面影响.
结论:
- 在实证研究中,PAWC在统计学上比SEM更有效和强大,用于调解分析.
- 这些发现挑战了先前比较SEM和PAWC的结论,强调了SNR的实用性.
- 了解预测器-调解器关系和预测错误的影响是最佳方法选择的关键.
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