方法对比
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| 序数探索性因子分析× | 结构方程模型× | |
|---|---|---|
| 领域≠ | 心理测量学 | 研究统计学 |
| 方法族≠ | Latent structure | Process / pipeline |
| 起源年份≠ | 1978–1984 | 1921 |
| 提出者≠ | Bengt Muthén | Sewall Wright |
| 类型≠ | Latent variable / dimension reduction | Method |
| 开创性文献≠ | Flora, D. B. & Curran, P. J. (2004). An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data. Psychological Methods, 9(4), 466–491. DOI ↗ | Jöreskog, K. G., & Sörbom, D. (1973). LISREL: A general computer program for estimating a linear structural equation system. Research Bulletin 73-5. University of Stockholm. link ↗ |
| 别名 | ordinal factor analysis, polychoric EFA, categorical EFA, EFA for ordinal data | SEM, path analysis, latent variable modeling, causal modeling |
| 相关≠ | 5 | 3 |
| 摘要≠ | Ordinal exploratory factor analysis discovers latent factors underlying a set of ordinal items — typically Likert scales — by computing polychoric correlations among the items and then applying a weighted least squares estimator. It avoids the distortions that arise when continuous EFA methods are naively applied to ordered categorical responses. | Structural equation modeling (SEM) is a comprehensive statistical framework combining path analysis (Sewall Wright, 1921) and confirmatory factor analysis to test complex causal models linking observed and latent variables. Formalized by Jöreskog (1973) with LISREL software, SEM enables simultaneous estimation of measurement relationships (how variables measure latent constructs) and structural relationships (how constructs influence outcomes), making it powerful for theory testing in psychology, epidemiology, organizational research, and health sciences where complex mediation, moderation, and latent processes require integrated analysis. |
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