Process / pipelineClinical / epidemiology
贝叶斯病例交叉设计 — 采用贝叶斯推断的自匹配流行病学研究
贝叶斯病例交叉设计是一种自匹配流行病学方法,用于估计时变暴露对急性事件风险的瞬时影响。每个病例都作为自己的对照,从而消除了时间稳定个体特征造成的混杂。贝叶斯推断取代或补充了经典的条件逻辑回归,使得能够纳入先验知识、在稀疏数据中实现更稳定的估计,并通过后验分布进行全面的不确定性量化。
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来源
- Maclure, M. (1991). The case-crossover design: a method for studying transient effects on the risk of acute events. American Journal of Epidemiology, 133(2), 144–153. DOI: 10.1093/oxfordjournals.aje.a115853 ↗
- Janes, H., Sheppard, L., & Lumley, T. (2005). Case-crossover analyses of air pollution exposure data: referent selection strategies and their implications for bias. Epidemiology, 16(6), 717–726. DOI: 10.1097/01.ede.0000181315.18836.9d ↗
如何引用本页
ScholarGate. (2026, June 3). Bayesian Case-Crossover Study Design. ScholarGate. https://scholargate.app/zh/epidemiology/bayesian-case-crossover-design
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