방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 단축형 확인적 요인분석 (SF-CFA)× | 문항 반응 이론 (IRT)× | |
|---|---|---|
| 분야 | 심리측정학 | 심리측정학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도≠ | 1990s–2000s | 1952–1968 |
| 창시자≠ | Building on CFA methodology (Jöreskog, 1969) applied to abbreviated scale contexts | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| 유형≠ | Confirmatory latent-variable model | Probabilistic measurement model |
| 원전≠ | Byrne, B. M. (2008). Structural Equation Modeling with EQS: Basic Concepts, Applications, and Programming (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805841268 | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| 별칭 | SF-CFA, abbreviated scale CFA, short-form validation, brief scale factor analysis | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| 관련≠ | 4 | 5 |
| 요약≠ | Short-form confirmatory factor analysis applies CFA to a reduced subset of items drawn from a longer validated scale, testing whether the abbreviated version preserves the original factor structure with acceptable model fit and reliability. It is a standard step in short-form scale development and validation. | 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 ↗ |
|
|