Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Investigación Longitudinal Multivariada× | Investigación de panel× | |
|---|---|---|
| Campo | Diseño de investigación | Diseño de investigación |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 1970s–1980s (formalized in behavioral sciences literature) | 1970s-1980s (econometric formalization); earlier social survey use from 1940s |
| Autor original≠ | Nesselroade, Baltes, and the developmental/behavioral sciences tradition | Social science and econometric traditions; systematized by Cheng Hsiao and others from the 1970s-1980s |
| Tipo≠ | Quantitative observational research design | Quantitative longitudinal observational design |
| Fuente seminal≠ | Nesselroade, J. R., & Baltes, P. B. (Eds.). (1979). Longitudinal Research in the Study of Behavior and Development. Academic Press. ISBN: 978-0125154505 | Hsiao, C. (2003). Analysis of Panel Data (2nd ed.). Cambridge University Press. ISBN: 978-0521522717 |
| Alias | longitudinal multivariate design, MLR, multivariate panel study, multivariate repeated-measures design | panel study, panel survey, longitudinal panel, repeated-measures panel |
| Relacionados≠ | 4 | 3 |
| Resumen≠ | Multivariate longitudinal research is a quantitative observational design that follows the same units — individuals, groups, or organizations — across two or more time points while measuring several outcome and predictor variables simultaneously. By combining the temporal dimension of longitudinal tracking with multivariate statistical analysis, it allows researchers to examine how a system of variables co-evolves, how early measures predict later outcomes across multiple domains, and whether relationships among variables are stable or change over time. | Panel research is a quantitative longitudinal design in which the same individuals, organizations, or other units are measured repeatedly across two or more time points. Unlike cross-sectional surveys that capture a single snapshot, a panel tracks change within units, enabling researchers to separate genuine within-unit change from between-unit differences and to model causal dynamics over time. |
| ScholarGateConjunto de datos ↗ |
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