방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 다집단 척도 개발× | 확인적 요인 분석 (CFA)× | |
|---|---|---|
| 분야 | 심리측정학 | 심리측정학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도≠ | 1971 (multi-group CFA); 2000 (applied synthesis for scale development) | 1969 |
| 창시자≠ | Jöreskog, K. G. (multi-group SEM framework); systematised for scale development by Vandenberg & Lance (2000) | Karl Gustav Jöreskog |
| 유형≠ | Scale development / measurement model testing | Hypothesis-testing latent variable model |
| 원전≠ | Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4–70. DOI ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| 별칭 | MGSD, cross-group scale development, multi-sample scale development, comparative scale construction | CFA, confirmatory FA, measurement model, restricted factor analysis |
| 관련≠ | 6 | 4 |
| 요약≠ | Multi-group scale development constructs and validates a measurement scale simultaneously across two or more distinct populations or groups. The approach integrates standard item generation and factor-analytic procedures with a systematic hierarchy of measurement invariance tests to ensure that the resulting scale measures the same construct in the same way in every target group. | 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 ↗ |
|
|