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| 階層的確証研究× | 階層モデル検証研究× | |
|---|---|---|
| 分野 | 研究デザイン | 研究デザイン |
| 系統 | Process / pipeline | Process / pipeline |
| 提唱年≠ | 1980s–2000s | 1980s–1990s (Raudenbush & Bryk 1986; Muthen 1994) |
| 提唱者≠ | Raudenbush & Bryk; Hox; Goldstein | Stephen Raudenbush and Anthony Bryk (HLM); extended to multilevel SEM by Bengt Muthen |
| 種類 | Quantitative confirmatory research design | Quantitative confirmatory research design |
| 原典 | Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (2nd ed.). Sage. ISBN: 978-0761919049 | Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (2nd ed.). Sage. ISBN: 978-0761919049 |
| 別名 | multilevel confirmatory research, nested confirmatory design, hierarchical hypothesis-testing research, HCR | multilevel model testing, hierarchical SEM, nested model testing, HLM model testing |
| 関連 | 5 | 5 |
| 概要≠ | Hierarchical confirmatory research is a quantitative design that tests pre-specified hypotheses about relationships or group differences in data that have a natural nested (hierarchical) structure — such as students clustered within classrooms, patients within hospitals, or employees within organizations. By explicitly modeling the hierarchy, it avoids the inflation of Type I error that occurs when nested data are analyzed as though observations were independent. | Hierarchical 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. |
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