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| 강건 맥도날드 오메가× | 로버스트 크론바흐 알파× | |
|---|---|---|
| 분야 | 심리측정학 | 심리측정학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도≠ | 1999 (omega); robust variant formalized in 2000s–2010s | 2002–2016 |
| 창시자≠ | Roderick P. McDonald (omega); robust extension via robust SEM estimators (MLR, DWLS) | Derived from Lee J. Cronbach (1951); robust variants formalized by Yuan & Bentler (2002) and Zhang & Yuan (2016) |
| 유형≠ | Reliability coefficient | Robust reliability coefficient |
| 원전≠ | McDonald, R. P. (1999). Test theory: A unified treatment. Lawrence Erlbaum Associates. ISBN: 978-0805830408 | Yuan, K.-H., & Bentler, P. M. (2002). On robustness of the normal-theory based asymptotic distributions of three reliability coefficient estimates. Psychometrika, 67(2), 251–268. DOI ↗ |
| 별칭 | robust omega, omega total (robust), robust omega-total, robust composite reliability | robust alpha, outlier-resistant Cronbach's alpha, robust internal consistency, robust coefficient alpha |
| 관련≠ | 4 | 3 |
| 요약≠ | 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 Cronbach's alpha adapts the classical internal consistency coefficient to data that violate the assumption of multivariate normality or contain influential outliers. By replacing the conventional sample covariance matrix with a robust counterpart, it yields a reliability estimate that is resistant to distortion by non-normal response distributions, contaminated observations, or small violations of model assumptions common in applied psychometric work. |
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