Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Longitudinal DIF× | Analyse factorielle confirmatoire longitudinale× | |
|---|---|---|
| Domaine | Psychométrie | Psychométrie |
| Famille | Latent structure | Latent structure |
| Année d'origine≠ | 1980s–2000s | 1970s–1990s |
| Auteur d'origine≠ | Multiple contributors; foundational DIF methods by Lord (1980) extended to longitudinal designs | Karl Jöreskog (CFA framework); longitudinal extension by Wheaton, Muthén, and Alwin in the 1970s–1990s |
| Type≠ | Item-level bias detection across time | Longitudinal latent variable / measurement model |
| Source fondatrice≠ | Millsap, R. E., & Kwok, O. M. (2004). Evaluating the impact of partial factorial measurement invariance on selection in two groups. Psychological Methods, 9(1), 93–115. DOI ↗ | Widaman, K. F. & Reise, S. P. (1997). Exploring the measurement invariance of psychological instruments: Applications in the substance use domain. In K. J. Bryant, M. Windle & S. G. West (Eds.), The science of prevention: Methodological advances from alcohol and substance abuse research (pp. 281–324). American Psychological Association. link ↗ |
| Alias | longitudinal DIF, DIF across time, temporal DIF, longitudinal item bias | longitudinal CFA, repeated-measures CFA, longitudinal measurement model, panel CFA |
| Apparentées | 6 | 6 |
| Résumé≠ | Longitudinal differential item functioning detects whether individual test or scale items behave differently across measurement occasions for the same respondents. It extends standard DIF methodology to repeated-measures designs, ensuring that observed change scores genuinely reflect construct change rather than shifts in item characteristics over time. | Longitudinal confirmatory factor analysis (longitudinal CFA) applies a theoretically specified measurement model to data collected at two or more time points. Its primary purpose is to verify that a scale measures the same latent construct in the same way over time — a prerequisite for drawing valid conclusions about change from repeated-measures data. |
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