방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 종단 탐색적 요인 분석 (종단 EFA)× | 탐색적 요인 분석 (EFA)× | |
|---|---|---|
| 분야≠ | 심리측정학 | 통계학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도≠ | 1970s–1983 | — |
| 창시자≠ | John R. Nesselroade and colleagues (lifespan developmental tradition) | — |
| 유형≠ | Latent variable / dimension reduction across time | Latent variable / dimension reduction |
| 원전≠ | Nesselroade, J. R. (1983). Temporal selection and factor invariance in the study of development and change. In P. B. Baltes & O. G. Brim (Eds.), Life-Span Development and Behavior (Vol. 5, pp. 59–87). Academic Press. link ↗ | 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≠ | LEFA, longitudinal factor analysis, repeated-measures EFA, panel EFA | common factor analysis, açımlayıcı faktör analizi, factor analysis |
| 관련≠ | 6 | 4 |
| 요약≠ | Longitudinal EFA applies exploratory factor analysis separately at each measurement occasion — or jointly across occasions — to discover whether the same latent factor structure emerges over time and whether factor loadings remain stable across waves. It is the foundational data-driven approach for examining structural change and continuity in panel and developmental research. | 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 ↗ |
|
|