방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 다수준 검사-재검사 신뢰도× | 일반화가능성 이론 (G-Theory)× | |
|---|---|---|
| 분야 | 심리측정학 | 심리측정학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도≠ | 1979 (ICC foundation); multilevel extension: 1990s–2000s | 1963–1972 |
| 창시자≠ | Shrout & Fleiss (ICC foundation); multilevel extension by Goldstein, Snijders, and others | Lee J. Cronbach, Goldine Gleser, Harinder Nanda, Nageswari Rajaratnam |
| 유형≠ | Reliability estimation under hierarchical data | Variance-components reliability model |
| 원전≠ | Shrout, P. E. & Fleiss, J. L. (1979). Intraclass correlations: Uses in assessing rater reliability. Psychological Bulletin, 86(2), 420–428. DOI ↗ | Cronbach, L. J., Gleser, G. C., Nanda, H. & Rajaratnam, N. (1972). The Dependability of Behavioral Measurements: Theory of Generalizability for Scores and Profiles. Wiley. link ↗ |
| 별칭≠ | hierarchical test-retest reliability, multilevel ICC reliability, nested test-retest reliability, ML-TRT reliability | G-theory, G-study / D-study framework, variance components reliability |
| 관련≠ | 5 | 4 |
| 요약≠ | Multilevel test-retest reliability estimates how consistently a measurement instrument produces the same scores across repeated administrations when observations are nested within higher-level units — such as patients within clinics or students within classrooms. It partitions total score variance across levels using intraclass correlation coefficients derived from multilevel models. | Generalizability Theory is a psychometric framework that decomposes observed score variance into multiple sources — persons, items, raters, occasions, and their interactions — using analysis of variance. It replaces the single reliability coefficient of classical test theory with a family of coefficients that tell researchers how well scores generalize across different measurement conditions. |
| ScholarGate데이터셋 ↗ |
|
|