Confronta i metodi
Esamina i metodi selezionati fianco a fianco; le righe che differiscono sono evidenziate.
| Ricerca longitudinale di coorte× | Ricerca Longitudinale× | |
|---|---|---|
| Campo | Disegno della ricerca | Disegno della ricerca |
| Famiglia | Process / pipeline | Process / pipeline |
| Anno di origine≠ | 1950s–1960s (formalized in epidemiological methodology) | Late 19th–early 20th century; methodologically codified through the 20th century |
| Ideatore≠ | Richard Doll & Austin Bradford Hill (landmark Doctors' Cohort Study, 1951); cohort logic formalized in mid-20th century epidemiology | No single originator; foundational methodological treatments by Stuart Menard and Judith Singer & John Willett |
| Tipo≠ | Quantitative observational longitudinal design | Quantitative (or mixed) observational research design |
| Fonte seminale≠ | Kelsey, J. L., Whittemore, A. S., Evans, A. S., & Thompson, W. D. (1996). Methods in Observational Epidemiology (2nd ed.). Oxford University Press. ISBN: 978-0195083439 | Menard, S. (2002). Longitudinal Research (2nd ed.). Sage Publications. ISBN: 978-0761922841 |
| Alias | longitudinal cohort study, prospective cohort study, cohort follow-up study, panel cohort design | longitudinal study, longitudinal design, prospective longitudinal study, repeated-measures observational study |
| Correlati≠ | 2 | 4 |
| Sintesi≠ | Longitudinal cohort research is an observational quantitative design that recruits a defined group of individuals sharing a common characteristic (the cohort) and follows them prospectively over time, collecting data at multiple points to examine how outcomes develop, risks accumulate, or relationships change. It is the cornerstone design for studying causation, developmental trajectories, and the natural history of phenomena in epidemiology, social science, and education. | 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. |
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