Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Validez discriminante robusta× | Modelado de Ecuaciones Estructurales× | |
|---|---|---|
| Campo≠ | Psicometría | Estadística para la investigación |
| Familia≠ | Latent structure | Process / pipeline |
| Año de origen≠ | 1959 (foundational); 2015 (HTMT criterion) | 1921 |
| Autor original≠ | Henseler, Ringle & Sarstedt (HTMT); Campbell & Fiske (foundational framework) | Sewall Wright |
| Tipo≠ | Validity assessment / measurement quality criterion | Method |
| Fuente seminal≠ | Henseler, J., Ringle, C. M. & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. DOI ↗ | 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 ↗ |
| Alias | HTMT criterion, heterotrait-monotrait ratio, discriminant validity testing, RDV | SEM, path analysis, latent variable modeling, causal modeling |
| Relacionados≠ | 4 | 3 |
| Resumen≠ | Robust discriminant validity assessment determines whether distinct latent constructs in a measurement model are sufficiently different from one another. Unlike traditional AVE-based approaches, robust methods such as the Heterotrait-Monotrait (HTMT) ratio use the pattern of inter-indicator correlations to provide a more sensitive and simulation-validated criterion for judging discriminant validity in structural equation modeling contexts. | 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. |
| ScholarGateConjunto de datos ↗ |
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