方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 多类别信度分析× | 验证性因子分析（CFA）× | |
|---|---|---|
| 领域 | 心理测量学 | 心理测量学 |
| 方法族 | Latent structure | Latent structure |
| 起源年份≠ | 2007–2009 (formal ordinal extensions); broader framework since 1950s | 1969 |
| 提出者≠ | Building on Cronbach (1951) and McDonald (1978); ordinal extensions by Zumbo and colleagues (2007) and Green and Yang (2009) | Karl Gustav Jöreskog |
| 类型≠ | Reliability estimation | Hypothesis-testing latent variable model |
| 开创性文献≠ | Green, S. B. & Yang, Y. (2009). Reliability of summed item scores using structural equation modeling: An alternative to coefficient alpha. Psychometrika, 74(1), 155–167. DOI ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| 别名 | polytomous scale reliability, ordinal reliability estimation, reliability for ordered-category items, polychoric reliability analysis | CFA, confirmatory FA, measurement model, restricted factor analysis |
| 相关≠ | 3 | 4 |
| 摘要≠ | Polytomous reliability analysis estimates the internal consistency or precision of measurement for scales composed of items with more than two ordered response categories, such as Likert-type, rating, or partial-credit items. It corrects a well-known underestimation bias in conventional Cronbach's alpha by working with polychoric correlations or IRT-based precision indices. | Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing. |
| ScholarGate数据集 ↗ |
|
|