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| Анализ на латентните преходи× | Частично най-малки квадрати - Моделиране на структурни уравнения× | |
|---|---|---|
| Област | Психометрия | Психометрия |
| Семейство | Latent structure | Latent structure |
| Година на възникване≠ | 2002 | 1985 |
| Създател≠ | Linda M. Collins, Stephanie T. Lanza | Herman Wold |
| Тип≠ | Markovian transition between latent states | Component-based structural equation model |
| Основополагащ източник≠ | Collins, L. M., & Lanza, S. T. (2010). Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences. Wiley. ISBN: 9780470228395 | Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (2nd ed.). Sage Publications. ISBN: 9781483377445 |
| Други названия≠ | LTA | PLS-SEM, PLS path modeling |
| Свързани≠ | 4 | 5 |
| Резюме≠ | Latent Transition Analysis (LTA) is a method for studying transitions between latent classes over time, developed by Collins and Lanza (2010). LTA combines latent class analysis (grouping individuals into classes) with Markovian transition models to understand how people move between qualitatively distinct states across time periods. | PLS-SEM is a variance-based approach to structural equation modeling developed by Herman Wold (1985) that estimates latent variable models by maximizing the variance explained in dependent variables. Unlike covariance-based SEM, PLS-SEM is particularly useful for exploratory research, small to medium samples, complex models with many constructs, and non-normal data. |
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