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| 다집단 척도 개발× | 다집단 확인적 요인분석 (MG-CFA)× | |
|---|---|---|
| 분야 | 심리측정학 | 심리측정학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도≠ | 1971 (multi-group CFA); 2000 (applied synthesis for scale development) | 1971 |
| 창시자≠ | Jöreskog, K. G. (multi-group SEM framework); systematised for scale development by Vandenberg & Lance (2000) | Karl Jöreskog |
| 유형≠ | Scale development / measurement model testing | Measurement model / invariance test |
| 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 ↗ | 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 ↗ |
| 별칭 | MGSD, cross-group scale development, multi-sample scale development, comparative scale construction | MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA |
| 관련 | 6 | 6 |
| 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. | Multi-group confirmatory factor analysis tests whether a measurement model holds equivalently across two or more groups — such as cultures, genders, or time points. By imposing increasingly stringent equality constraints and comparing model fit, it determines whether comparisons of latent mean scores are justified. |
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