方法对比
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| 稳健麦克唐纳欧米伽× | 稳健的验证性因子分析× | |
|---|---|---|
| 领域≠ | 心理测量学 | 统计学 |
| 方法族 | Latent structure | Latent structure |
| 起源年份≠ | 1999 (omega); robust variant formalized in 2000s–2010s | 1984–1994 |
| 提出者≠ | Roderick P. McDonald (omega); robust extension via robust SEM estimators (MLR, DWLS) | Satorra & Bentler (robust SE/chi-square corrections); Browne (ADF estimator) |
| 类型≠ | Reliability coefficient | Confirmatory latent variable model with robust estimation |
| 开创性文献≠ | McDonald, R. P. (1999). Test theory: A unified treatment. Lawrence Erlbaum Associates. ISBN: 978-0805830408 | Satorra, A. & Bentler, P. M. (1994). Corrections to test statistics and standard errors in covariance structure analysis. In A. von Eye & C. C. Clogg (Eds.), Latent variables analysis: Applications for developmental research (pp. 399–419). Sage. link ↗ |
| 别名 | robust omega, omega total (robust), robust omega-total, robust composite reliability | Robust CFA, CFA with robust standard errors, Satorra-Bentler CFA, non-normal CFA |
| 相关≠ | 4 | 6 |
| 摘要≠ | Robust McDonald's omega estimates the internal consistency reliability of a composite scale using factor-analytic loadings obtained through robust estimation methods (such as MLR or DWLS). Unlike standard omega or Cronbach's alpha, it remains accurate when item distributions are non-normal, skewed, or when the sample contains influential outliers — conditions common in applied psychological and educational measurement. | Robust confirmatory factor analysis fits a pre-specified factor structure to observed data while correcting standard errors and goodness-of-fit statistics for violations of multivariate normality. It is the preferred variant of CFA whenever Likert-type, skewed, or kurtotic indicators make the classical normal-theory estimator unreliable. |
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