ScholarGate
어시스턴트

방법 비교

선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.

다집단 수렴 타당도×다집단 측정 불변성 검정×
분야심리측정학심리측정학
계열Latent structureLatent structure
기원 연도1981 / 20001971–1993
창시자Fornell & Larcker (convergent validity criteria); Vandenberg & Lance (multi-group extension)Jöreskog, K. G. (1971); Meredith, W. (1993)
유형Validity assessment procedureModel comparison / hypothesis testing
원전Fornell, C. & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. 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 ↗
별칭cross-group convergent validity, multi-sample convergent validity, MGCFA convergent validity, AVE across groupsmeasurement invariance, factorial invariance, cross-group invariance, MI testing
관련66
요약Multi-group convergent validity examines whether items purported to measure the same latent construct relate strongly to that construct consistently across distinct subgroups such as demographic categories, cultures, or experimental conditions. It extends single-sample convergent validity checks into a comparative multi-group confirmatory factor analysis framework.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
  1. v1
  2. 2 출처
  3. PUBLISHED
  1. v1
  2. 2 출처
  3. PUBLISHED

검색으로 이동 슬라이드 다운로드

ScholarGate방법 비교: Multi-group convergent validity · Multi-group measurement invariance. 2026-06-18에 다음에서 검색함: https://scholargate.app/ko/compare