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| 다집단 문항 반응 함수 (MG-DIF)× | 다집단 측정 불변성 검정× | |
|---|---|---|
| 분야 | 심리측정학 | 심리측정학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도≠ | 1980s-1990s | 1971–1993 |
| 창시자≠ | Shealy & Stout (SIBTEST framework); Lord (IRT-based DIF) | Jöreskog, K. G. (1971); Meredith, W. (1993) |
| 유형≠ | Measurement bias detection | Model comparison / hypothesis testing |
| 원전≠ | Millsap, R. E. (2012). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936 | 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 | MG-DIF, multi-group DIF, differential item functioning across groups, multiple-group DIF analysis | measurement invariance, factorial invariance, cross-group invariance, MI testing |
| 관련 | 6 | 6 |
| 요약≠ | Multi-group differential item functioning examines whether test or scale items function equivalently across three or more distinct groups — such as gender, ethnicity, or country — after matching respondents on the underlying trait being measured. Items that behave differently across groups threaten fair measurement and valid score comparisons. | Multi-group measurement invariance testing examines whether a latent construct is measured in the same way across two or more distinct groups — such as cultures, genders, or age cohorts. It is a prerequisite for meaningful group comparisons of latent means or relationships, ensuring that observed score differences reflect true differences rather than measurement artifacts. |
| ScholarGate데이터셋 ↗ |
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