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| Studio di coorte Bayesiano× | Studio caso-controllo nidificato× | |
|---|---|---|
| Campo | Epidemiologia | Epidemiologia |
| Famiglia | Process / pipeline | Process / pipeline |
| Anno di origine≠ | 1990s–2000s (widespread adoption in epidemiology) | 1973–1977 |
| Ideatore≠ | Bayesian framework: Thomas Bayes / Pierre-Simon Laplace; applied to cohort epidemiology from the 1990s onward | Nathan Mantel (1973); D. C. Thomas (1977 formalization) |
| Tipo≠ | Observational longitudinal study with Bayesian inference | Hybrid observational study design |
| Fonte seminale≠ | Spiegelhalter, D. J., Abrams, K. R., & Myles, J. P. (2004). Bayesian Approaches to Clinical Trials and Health-Care Evaluation. Wiley. ISBN: 978-0471499756 | Thomas, D. C. (1977). Addendum to: Methods of cohort analysis: Appraisal by application to asbestos mining. Journal of the Royal Statistical Society, Series A, 140(4), 469–491. link ↗ |
| Alias | Bayesian longitudinal cohort, Bayesian prospective cohort, Bayesian cohort analysis, Bayesian follow-up study | NCC study, nested CC design, case-control within cohort, density sampling case-control |
| Correlati≠ | 5 | 6 |
| Sintesi≠ | A Bayesian cohort study follows a defined group of individuals over time to estimate incidence, risk, or rate of outcomes, while using Bayesian statistical inference to incorporate prior knowledge and quantify uncertainty through posterior probability distributions rather than classical p-values and confidence intervals. It combines the longitudinal observational design of a cohort study with the probability-updating logic of Bayesian analysis, allowing richer uncertainty quantification and sequential updating as data accumulate. | A nested case-control study is an efficient observational design embedded within a defined cohort. For each participant who develops the outcome of interest (a case), a small number of matched controls are sampled from those still at risk at the same point in time. This density-sampling strategy yields odds ratios that approximate incidence-rate ratios from the full cohort at a fraction of the data-collection cost — making it the preferred alternative when measuring exposures for all cohort members would be prohibitively expensive or technically demanding. |
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