Process / pipelineClinical / epidemiology
贝叶斯生态学研究 — 贝叶斯疾病制图与生态回归
贝叶斯生态学研究将经典生态流行病学的群体水平观察设计与贝叶斯分层建模相结合。它不将疾病率视为固定量，而是对潜在的空间或时间效应设定先验分布（通常使用 Besag-York-Mollié (BYM) 卷积先验），并从汇总数据中更新信念，以生成疾病风险的后验图、平滑的率估计以及暴露与结局之间生态关联的可信区间。
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来源
- Lawson, A. B. (2013). Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology (2nd ed.). CRC Press. ISBN: 978-1466504813
- Besag, J., York, J., & Mollie, A. (1991). Bayesian image restoration, with two applications in spatial statistics. Annals of the Institute of Statistical Mathematics, 43(1), 1–20. DOI: 10.1007/BF00116466 ↗
如何引用本页
ScholarGate. (2026, June 3). Bayesian Ecological Study Design. ScholarGate. https://scholargate.app/zh/epidemiology/bayesian-ecological-study
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