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분야연구설계연구설계
계열Process / pipelineProcess / pipeline
기원 연도1980s–1990s (Raudenbush & Bryk 1986; Muthen 1994)1970s (Joreskog 1969–1973); widely adopted in social sciences by the 1980s–1990s
창시자Stephen Raudenbush and Anthony Bryk (HLM); extended to multilevel SEM by Bengt MuthenKarl G. Joreskog (SEM/LISREL framework); formalized through structural equation modeling tradition
유형Quantitative confirmatory research designConfirmatory quantitative research design
원전Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (2nd ed.). Sage. ISBN: 978-0761919049Kline, R. B. (2015). Principles and Practice of Structural Equation Modeling (4th ed.). Guilford Press. ISBN: 978-1462523344
별칭multilevel model testing, hierarchical SEM, nested model testing, HLM model testingmodel-based research, structural model testing, theory-testing research, MTR
관련55
요약Hierarchical model testing research is a quantitative design that evaluates theoretically derived models using data with a nested or clustered structure — for example, students within classrooms, employees within organisations, or patients within hospitals. It applies hierarchical linear models (HLM) or multilevel structural equation models (ML-SEM) to test whether a proposed set of relationships holds after properly accounting for the non-independence introduced by grouping.Model testing research is a confirmatory quantitative design in which the researcher specifies a theoretical model — depicting hypothesized relationships among constructs — and then tests how well that model fits empirical data. Drawing primarily on structural equation modeling (SEM) and confirmatory factor analysis (CFA), it evaluates whether the data-implied covariance structure is consistent with the theoretically derived one, yielding fit indices that indicate model-data correspondence.
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ScholarGate방법 비교: Hierarchical Model Testing Research · Model Testing Research. 2026-06-17에 다음에서 검색함: https://scholargate.app/ko/compare