Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Investigación de cohortes basada en paneles× | Investigación Longitudinal× | |
|---|---|---|
| Campo | Diseño de investigación | Diseño de investigación |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | Mid-20th century (formalized ~1950s–1970s) | Late 19th–early 20th century; methodologically codified through the 20th century |
| Autor original≠ | Developed through convergence of epidemiological cohort methodology and social science panel survey traditions | No single originator; foundational methodological treatments by Stuart Menard and Judith Singer & John Willett |
| Tipo≠ | Quantitative longitudinal observational design | Quantitative (or mixed) observational research design |
| Fuente seminal≠ | Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. ISBN: 978-1107038691 | Menard, S. (2002). Longitudinal Research (2nd ed.). Sage Publications. ISBN: 978-0761922841 |
| Alias | panel cohort study, longitudinal panel cohort, cohort panel design, panel longitudinal study | longitudinal study, longitudinal design, prospective longitudinal study, repeated-measures observational study |
| Relacionados≠ | 3 | 4 |
| Resumen≠ | Panel-based cohort research is a longitudinal observational design that follows a defined group of individuals — the cohort — across multiple repeated measurement waves, collecting structured quantitative data at each wave. It merges the epidemiological strength of cohort tracking (a group sharing a common characteristic or entry point) with the panel study convention of standardized, repeated-contact data collection. The design enables analysis of change over time within individuals while supporting causal inference about exposure-outcome relationships. | Longitudinal research is an observational design in which the same participants, groups, or units are measured repeatedly over an extended period. Rather than capturing a single snapshot, it tracks change, stability, and temporal sequencing of variables — making it the primary non-experimental strategy for studying development, growth, decline, and the unfolding of causal processes across time. |
| ScholarGateConjunto de datos ↗ |
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