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| 다수준 라쉬 모형× | 다층 확인적 요인분석 (Multilevel Confirmatory Factor Analysis, MCFA)× | |
|---|---|---|
| 분야 | 심리측정학 | 심리측정학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도≠ | 1997 | 1994 |
| 창시자≠ | Adams, Wilson & Wu | Bengt O. Muthen |
| 유형≠ | Hierarchical item response model | Latent variable model / measurement model |
| 원전≠ | Adams, R. J., Wilson, M. & Wu, M. (1997). Multilevel item response models: An approach to errors in variables regression. Journal of Educational and Behavioral Statistics, 22(1), 47–76. DOI ↗ | Muthen, B. O. (1994). Multilevel covariance structure analysis. Sociological Methods & Research, 22(3), 376–398. DOI ↗ |
| 별칭 | hierarchical Rasch model, random-effects Rasch model, multilevel IRT Rasch, MRCML model | MCFA, multilevel measurement model, two-level CFA, hierarchical CFA |
| 관련≠ | 5 | 6 |
| 요약≠ | The multilevel Rasch model extends the standard Rasch model to data with a nested structure — for example, students within classrooms within schools — by embedding person ability parameters inside a hierarchical linear model. It yields item difficulty estimates on a logit scale while simultaneously partitioning person-ability variance across cluster levels and correcting standard errors for non-independence. | Multilevel confirmatory factor analysis tests a pre-specified factor structure while simultaneously accounting for the non-independence of observations caused by clustered data. It decomposes item variance into within-group and between-group components, fitting a separate measurement model at each level, making it the standard tool for validating psychometric scales administered within natural groups such as classrooms, clinics, or organisations. |
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