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| Longitudinale Kohortenforschung× | Panelstudien× | |
|---|---|---|
| Fachgebiet | Forschungsdesign | Forschungsdesign |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr≠ | 1950s–1960s (formalized in epidemiological methodology) | 1970s-1980s (econometric formalization); earlier social survey use from 1940s |
| Urheber≠ | Richard Doll & Austin Bradford Hill (landmark Doctors' Cohort Study, 1951); cohort logic formalized in mid-20th century epidemiology | Social science and econometric traditions; systematized by Cheng Hsiao and others from the 1970s-1980s |
| Typ≠ | Quantitative observational longitudinal design | Quantitative longitudinal observational design |
| Wegweisende Quelle≠ | 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 | Hsiao, C. (2003). Analysis of Panel Data (2nd ed.). Cambridge University Press. ISBN: 978-0521522717 |
| Aliasnamen | longitudinal cohort study, prospective cohort study, cohort follow-up study, panel cohort design | panel study, panel survey, longitudinal panel, repeated-measures panel |
| Verwandt≠ | 2 | 3 |
| Zusammenfassung≠ | 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. | 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. |
| ScholarGateDatensatz ↗ |
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