방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 검사 동등화× | 확인적 요인 분석 (CFA)× | |
|---|---|---|
| 분야 | 심리측정학 | 심리측정학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도≠ | 1984 (modern statistical treatment) | 1969 |
| 창시자≠ | Kolen & Brennan (foundational treatise, 2004/2014); Holland & Dorans (2006) | Karl Gustav Jöreskog |
| 유형≠ | Score transformation / latent-scale calibration | Hypothesis-testing latent variable model |
| 원전≠ | Kolen, M.J. & Brennan, R.L. (2014). Test Equating, Scaling, and Linking: Methods and Practices (3rd ed.). Springer. ISBN: 978-1-4939-0316-6 | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| 별칭≠ | Test Eşitleme (Test Equating), score equating, equipercentile equating, IRT true-score equating | CFA, confirmatory FA, measurement model, restricted factor analysis |
| 관련 | 4 | 4 |
| 요약≠ | Test equating is a family of statistical methods that converts scores earned on one test form onto the score scale of another form, so that scores from different administrations or versions can be compared and reported on a common metric. The foundational modern treatment is Kolen and Brennan (2004/2014); Holland and Dorans (2006) provide the authoritative chapter-length overview within the field of educational measurement. | Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing. |
| ScholarGate데이터셋 ↗ |
|
|