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| 多类别信度分析× | ordinal reliability analysis× | |
|---|---|---|
| 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 | 2007 |
| 提出者≠ | Building on Cronbach (1951) and McDonald (1978); ordinal extensions by Zumbo and colleagues (2007) and Green and Yang (2009) | Bruno D. Zumbo and colleagues |
| 类型≠ | Reliability estimation | Internal consistency reliability estimation |
| 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 ↗ | Zumbo, B. D., Gadermann, A. M. & Zeisser, C. (2007). Ordinal versions of coefficients alpha and theta as measures of internal consistency for Likert rating scales. Journal of Modern Applied Statistical Methods, 6(1), 21–29. DOI ↗ |
| 别名 | polytomous scale reliability, ordinal reliability estimation, reliability for ordered-category items, polychoric reliability analysis | ordinal alpha, polychoric reliability, reliability for ordinal scales, ORA |
| 相关≠ | 3 | 5 |
| 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. | Ordinal reliability analysis estimates the internal consistency of scales whose items are measured on ordered-category (Likert-type) response formats. By basing computations on polychoric correlations rather than Pearson correlations, it corrects for the attenuation that standard Cronbach's alpha produces when responses are discrete and non-normal. |
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