Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Investigación de pruebas de modelos basadas en paneles× | Modelado de Ecuaciones Estructurales× | |
|---|---|---|
| Campo≠ | Diseño de investigación | Estadística para la investigación |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 1970s–1980s (panel econometrics and SEM matured in parallel) | 1921 |
| Autor original≠ | Developed across econometrics (Hsiao, Hausman) and psychometrics (Jöreskog, Bollen) | Sewall Wright |
| Tipo≠ | Quantitative longitudinal research design | Method |
| Fuente seminal≠ | Bollen, K. A. (1989). Structural Equations with Latent Variables. Wiley. ISBN: 978-0471011712 | 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 | panel SEM, longitudinal model testing, panel structural equation modeling, panel-based hypothesis testing | SEM, path analysis, latent variable modeling, causal modeling |
| Relacionados≠ | 4 | 3 |
| Resumen≠ | Panel-based model testing research combines the longitudinal power of panel survey designs with the confirmatory rigor of structural model testing — such as structural equation modeling (SEM), path analysis, or confirmatory factor analysis — applied to data collected from the same units (individuals, firms, countries) across multiple time points. This approach enables researchers to test theoretically specified causal and mediation structures while controlling for unobserved unit-level heterogeneity and examining how relationships unfold over time. | 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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