方法对比
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| 贝叶斯巢式病例对照研究× | 队列研究× | |
|---|---|---|
| 领域 | 流行病学 | 流行病学 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1977 (nested case-control); Bayesian adaptation developed through 1990s–2010s | Mid-20th century (formal epidemiological design codified ~1950s) |
| 提出者≠ | Nested case-control: D. C. Thomas (1977); Bayesian extension: various authors in biostatistics | Doll & Hill (British Doctors Study, 1951); Snow (cholera, 1854) |
| 类型≠ | Observational analytical study design with Bayesian inference | Observational longitudinal study design |
| 开创性文献≠ | 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 ↗ | Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641 |
| 别名≠ | Bayesian NCC, Bayesian nested case-referent study, Bayesian sampled case-control within cohort | longitudinal study, follow-up study, panel study, incidence study |
| 相关≠ | 5 | 6 |
| 摘要≠ | A Bayesian nested case-control study embeds a case-control sampling scheme within a defined prospective cohort and then estimates exposure-outcome associations using Bayesian inference. Cases are individuals in the cohort who develop the outcome of interest; controls are sampled from the risk set at the time each case is identified. The Bayesian framework allows incorporation of prior knowledge — from earlier studies, expert opinion, or biological plausibility — and produces full posterior distributions for effect estimates rather than single-point estimates with confidence intervals. | A 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. |
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