Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Schéma cas-co-cohorte× | Modélisation par équations structurelles par moindres carrés partiels× | |
|---|---|---|
| Domaine | Psychométrie | Psychométrie |
| Famille | Latent structure | Latent structure |
| Année d'origine≠ | 1986 | 1985 |
| Auteur d'origine≠ | Ross Prentice | Herman Wold |
| Type≠ | Partial cohort sampling design | Component-based structural equation model |
| Source fondatrice≠ | Prentice, R. L. (1986). A case-cohort design for epidemiologic cohort studies and disease prevention trials. Biometrika, 73(1), 1-11. DOI ↗ | 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 |
| Alias≠ | — | PLS-SEM, PLS path modeling |
| Apparentées≠ | 4 | 5 |
| Résumé≠ | Case-cohort design is an epidemiological study design developed by Prentice (1986) that efficiently combines features of case-control and cohort studies. Researchers enroll an entire cohort, follow it for outcomes, then measure exposures only on cases and a random subcohort, reducing measurement costs while maintaining valid causal inference. | 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. |
| ScholarGateJeu de données ↗ |
|
|