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| Mô hình phương trình cấu trúc (SEM)× | Phân tích nhân tố khẳng định (Confirmatory Factor Analysis - CFA)× | Phân tích trung gian× | |
|---|---|---|---|
| Lĩnh vực≠ | Thống kê | Trắc lượng tâm lý | Thống kê |
| Họ≠ | Latent structure | Latent structure | Hypothesis test |
| Năm ra đời≠ | 1970 | 1969 | 1986 |
| Người khởi xướng≠ | Karl Jöreskog (LISREL framework, 1970s) | Karl Gustav Jöreskog | Baron & Kenny |
| Loại≠ | Latent variable / causal modeling | Hypothesis-testing latent variable model | Indirect effects / path test |
| Công trình gốc≠ | Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning. ISBN: 978-1473756540 | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ | Baron, R. M. & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research. Journal of Personality and Social Psychology, 51(6), 1173–1182. link ↗ |
| Tên gọi khác | Yapısal Eşitlik Modellemesi (SEM), structural equation modelling, covariance structure analysis, latent variable modeling | CFA, confirmatory FA, measurement model, restricted factor analysis | indirect effects analysis, path-based mediation, PROCESS macro mediation, Aracılık Analizi (Mediation / PROCESS) |
| Liên quan≠ | 5 | 4 | 5 |
| Tóm tắt≠ | 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. | 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. | Mediation analysis is a statistical procedure that tests whether the effect of an independent variable X on an outcome Y operates wholly or partly through a third variable M, called the mediator. Formalised by Baron and Kenny in 1986, it decomposes the total effect of X on Y into a direct path (c′) and an indirect path (a × b), quantifying how much of the relationship is carried by the mediating mechanism. |
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