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Bayesian estimation of a cancer population by capture-recapture with individual capture heterogeneity and small sample

机译:通过具有个体捕获异质性和少量样本的捕获-捕获来对癌症种群进行贝叶斯估计

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摘要

BackgroundCancer incidence and prevalence estimates are necessary to inform health policy, to predict public health impact and to identify etiological factors. Registers have been used to estimate the number of cancer cases. To be reliable and useful, cancer registry data should be complete. Capture-recapture is a method for estimating the number of cases missed, originally developed in ecology to estimate the size of animal populations. Capture recapture methods in cancer epidemiology involve modelling the overlap between lists of individuals using log-linear models. These models rely on assumption of independence of sources and equal catchability between individuals, unlikely to be satisfied in cancer population as severe cases are more likely to be captured than simple cases.
机译:背景癌症发病率和患病率估计对于制定卫生政策,预测公共卫生影响和确定病因是必不可少的。寄存器已用于估计癌症病例的数量。为了可靠和有用,癌症登记数据应完整。捕获再捕获是一种估计遗漏病例数的方法,最初是在生态学中发展起来的,用于估计动物种群的大小。癌症流行病学中的捕获重获方法涉及使用对数线性模型对个体列表之间的重叠进行建模。这些模型依赖于源的独立性和个体之间相等的可捕获性的假设,这在癌症人群中不太可能得到满足,因为与简单病例相比,更可能捕获严重病例。

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