방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 문항반응이론(IRT) 기반 컴퓨터 적응 검사 (CAT-IRT)× | 탐색적 요인 분석 (EFA)× | |
|---|---|---|
| 분야≠ | 심리측정학 | 통계학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도≠ | 1970s–1980s | — |
| 창시자≠ | Lord, F. M.; further developed by Wainer, van der Linden, and others | — |
| 유형≠ | Adaptive measurement / sequential testing | Latent variable / dimension reduction |
| 원전≠ | Wainer, H. (Ed.). (2000). Computerized Adaptive Testing: A Primer (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805835113 | Fabrigar, L. R., Wegener, D. T., MacCallum, R. C. & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299. DOI ↗ |
| 별칭≠ | CAT-IRT, adaptive testing, IRT-based CAT, computerized adaptive testing | common factor analysis, açımlayıcı faktör analizi, factor analysis |
| 관련 | 4 | 4 |
| 요약≠ | Computerized adaptive testing based on item response theory is a sequential measurement procedure in which a computer algorithm selects successive test items tailored to each examinee's estimated ability level. Drawing on IRT to model item characteristics and ability estimation, CAT delivers precise scores with far fewer items than fixed-length tests, making it efficient for high-stakes assessments, clinical screening, and large-scale surveys. | Exploratory factor analysis reduces a large set of observed variables into a smaller number of latent common factors. It is widely used in scale development and psychometrics to uncover the dimensional structure that underlies a set of correlated items, without specifying that structure in advance. |
| ScholarGate데이터셋 ↗ |
|
|