方法对比

	贝叶斯巢式病例对照研究	嵌套病例对照研究
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	1973–1977
提出者	Nested case-control: D. C. Thomas (1977); Bayesian extension: various authors in biostatistics	Nathan Mantel (1973); D. C. Thomas (1977 formalization)
类型	Observational analytical study design with Bayesian inference	Hybrid observational 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.	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.
别名	Bayesian NCC, Bayesian nested case-referent study, Bayesian sampled case-control within cohort	NCC study, nested CC design, case-control within cohort, density sampling case-control
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 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.