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| 다항 신뢰도 분석× | 문항 반응 이론 (IRT)× | |
|---|---|---|
| 분야 | 심리측정학 | 심리측정학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도≠ | 2007–2009 (formal ordinal extensions); broader framework since 1950s | 1952–1968 |
| 창시자≠ | Building on Cronbach (1951) and McDonald (1978); ordinal extensions by Zumbo and colleagues (2007) and Green and Yang (2009) | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| 유형≠ | Reliability estimation | Probabilistic measurement model |
| 원전≠ | 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 ↗ | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| 별칭 | polytomous scale reliability, ordinal reliability estimation, reliability for ordered-category items, polychoric reliability analysis | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| 관련≠ | 3 | 5 |
| 요약≠ | 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. | Item response theory models the probability that a respondent answers an item correctly (or endorses it) as a function of the respondent's latent trait level and the item's own statistical properties — difficulty, discrimination, and guessing. Unlike classical test theory, IRT places persons and items on the same scale, yielding measurement that is sample-independent for items and test-independent for persons. |
| ScholarGate데이터셋 ↗ |
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