Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Ієрархічне лінійне моделювання (ІЛМ / Багаторівневе моделювання)× | Дисперсійний аналіз повторних вимірювань× | Моделювання структурними рівняннями (SEM)× | |
|---|---|---|---|
| Галузь | Статистика | Статистика | Статистика |
| Родина≠ | Hypothesis test | Hypothesis test | Latent structure |
| Рік появи≠ | 1986 | 1992 | 1970 |
| Автор методу≠ | Raudenbush & Bryk (popularized); Goldstein (parallel development) | Girden (textbook treatment); Field (2013) | Karl Jöreskog (LISREL framework, 1970s) |
| Тип≠ | Parametric nested-data regression | Parametric within-subjects mean comparison | Latent variable / causal modeling |
| Основоположне джерело≠ | Raudenbush, S.W. & Bryk, A.S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (2nd ed.). Sage. ISBN: 978-0761919049 | Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed., Ch. 14). SAGE. ISBN: 978-1446249185 | Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning. ISBN: 978-1473756540 |
| Інші назви≠ | HLM, MLM, multilevel modeling, multilevel analysis | within-subjects ANOVA, repeated measures analysis of variance, rm-ANOVA, Tekrarlı Ölçüm ANOVA | Yapısal Eşitlik Modellemesi (SEM), structural equation modelling, covariance structure analysis, latent variable modeling |
| Пов'язані≠ | 4 | 4 | 5 |
| Підсумок≠ | Hierarchical Linear Modeling (HLM), also known as Multilevel Modeling (MLM), is a parametric statistical method for analyzing nested or clustered data — for example students within classrooms, patients within hospitals, or employees within organizations. Formalized by Raudenbush and Bryk in their 2002 seminal text (building on work from the mid-1980s), HLM simultaneously estimates individual-level and group-level effects while correctly partitioning variance across levels. | Repeated-measures ANOVA is a parametric hypothesis test that compares three or more measurements taken from the same individuals — typically across time points or conditions — to decide whether their means differ. It extends one-way ANOVA to within-subjects designs, as treated in standard references such as Girden (1992) and Field (2013). | Structural equation modeling is a multivariate statistical framework that simultaneously estimates a measurement model — relating observed indicators to latent constructs — and a structural model specifying directional or reciprocal relationships among those constructs. Rooted in the LISREL tradition developed by Karl Jöreskog in the 1970s, SEM is the standard tool for testing complex theoretical models in the social, behavioural, and management sciences. |
| ScholarGateНабір даних ↗ |
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