Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Дослідження з тестування багатовимірних моделей× | Моделювання структурними рівняннями× | |
|---|---|---|
| Галузь≠ | Дизайн дослідження | Статистика досліджень |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи≠ | 1970s–1980s (multivariate model testing as a distinct approach) | 1921 |
| Автор методу≠ | Karl Jöreskog (SEM/LISREL framework); Barbara Tabachnick & Linda Fidell (multivariate methods synthesis) | Sewall Wright |
| Тип≠ | Quantitative confirmatory research design | Method |
| Основоположне джерело≠ | Tabachnick, B. G., & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson. ISBN: 978-0134790541 | Jöreskog, K. G., & Sörbom, D. (1973). LISREL: A general computer program for estimating a linear structural equation system. Research Bulletin 73-5. University of Stockholm. link ↗ |
| Інші назви | multivariate model testing, multivariate structural testing, multivariate confirmatory modeling, MVMT research | SEM, path analysis, latent variable modeling, causal modeling |
| Пов'язані≠ | 5 | 3 |
| Підсумок≠ | Multivariate model testing research is a confirmatory quantitative design in which a theoretically derived model involving multiple variables and their interrelationships is formally tested against empirical data. Rather than exploring patterns inductively, the researcher specifies a model a priori — capturing hypothesized directional paths, latent constructs, or covariance structures — and then evaluates how well this model reproduces the observed data using techniques such as structural equation modeling, confirmatory factor analysis, or multivariate path analysis. | Structural equation modeling (SEM) is a comprehensive statistical framework combining path analysis (Sewall Wright, 1921) and confirmatory factor analysis to test complex causal models linking observed and latent variables. Formalized by Jöreskog (1973) with LISREL software, SEM enables simultaneous estimation of measurement relationships (how variables measure latent constructs) and structural relationships (how constructs influence outcomes), making it powerful for theory testing in psychology, epidemiology, organizational research, and health sciences where complex mediation, moderation, and latent processes require integrated analysis. |
| ScholarGateНабір даних ↗ |
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