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Kohortstudie×tvärsnittsstudie inom epidemiologi×
ÄmnesområdeEpidemiologiEpidemiologi
FamiljProcess / pipelineProcess / pipeline
UrsprungsårMid-20th century (formal epidemiological design codified ~1950s)1960s (formal codification); widely practiced since mid-20th century
UpphovspersonDoll & Hill (British Doctors Study, 1951); Snow (cholera, 1854)Classical epidemiology tradition; systematized by Brian MacMahon and Thomas Pugh (1960s)
TypObservational longitudinal study designObservational, descriptive/analytic epidemiological design
UrsprungskällaRothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641Kelsey, J. L., Whittemore, A. S., Evans, A. S., & Thompson, W. D. (1996). Methods in Observational Epidemiology (2nd ed.). Oxford University Press. ISBN: 978-0195080407
Aliaslongitudinal study, follow-up study, panel study, incidence studyprevalence study, cross-sectional survey, transversal study, cross-sectional design
Närliggande66
SammanfattningA cohort study assembles a group of individuals who share a common starting point — typically freedom from the outcome of interest — and follows them over time to observe who develops the outcome. By comparing incidence rates between exposed and unexposed subgroups, researchers can estimate relative risk and absolute risk differences. Cohort studies are the gold-standard observational design for measuring disease incidence and establishing temporal relationships between exposure and outcome.A cross-sectional epidemiological study measures the exposure(s) and outcome(s) of interest simultaneously in a defined population at a single point in time (or over a short period). Because there is no follow-up, it is the most efficient observational design for estimating disease prevalence and for generating hypotheses about associations between risk factors and health outcomes.
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ScholarGateJämför metoder: Cohort Study · Cross-sectional epidemiological study. Hämtad 2026-06-18 från https://scholargate.app/sv/compare