مقایسهٔ روشها
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| تحلیل عاملی تأییدی (CFA)× | مدلسازی چندسطحی× | |
|---|---|---|
| حوزه≠ | روانسنجی | آمار پژوهش |
| خانواده≠ | Latent structure | Process / pipeline |
| سال پیدایش≠ | 1969 | 1992 |
| پدیدآور≠ | Karl Gustav Jöreskog | Anthony Bryk and Stephen Raudenbush |
| نوع≠ | Hypothesis-testing latent variable model | Method |
| منبع بنیادین≠ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ | Bryk, A. S., & Raudenbush, S. W. (1992). Hierarchical Linear Models: Applications and Data Analysis Methods. SAGE Publications. DOI ↗ |
| نامهای دیگر | CFA, confirmatory FA, measurement model, restricted factor analysis | HLM, mixed-effects models, random effects models, MLM |
| مرتبط≠ | 4 | 3 |
| خلاصه≠ | Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing. | Multilevel modeling (also called hierarchical linear modeling, mixed-effects modeling) is a statistical framework for analyzing data organized in nested or clustered structures—students within schools, patients within hospitals, repeated measures within individuals. Developed by Bryk and Raudenbush (1992), it accounts for dependency among observations and partitions variance into levels (within-cluster and between-cluster), enabling valid inference and revealing context effects. Essential in education, medicine, organizational research, and any field where data have natural hierarchies. |
| ScholarGateمجموعهداده ↗ |
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