在存在连续协变量的情况下,使用多系统估计量进行总体估计

E. Zwane, P. V. D. van der Heijden
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引用次数: 21

摘要

在存在连续协变量的情况下,标准的捕获-再捕获方法要么假设注册在个体水平上独立运行,要么假设协变量可以分层并拟合对数线性模型,从而允许对数据源之间的依赖性进行建模。本文介绍了一种方法,其中注册之间的直接依赖是建模留下连续协变量在其测量尺度。模拟表明,不考虑注册之间可能存在的依赖性会导致总体大小和标准误差的估计有偏。将该方法应用于荷兰神经管缺陷配准数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Population estimation using the multiple system estimator in the presence of continuous covariates
In the presence of continuous covariates, standard capture-recapture methods assume either that the registrations operate independently at the individual level or that the covariates can be stratified and log-linear models fitted, permitting the modelling of dependence between data sources. This article introduces an approach where direct dependence between registrations is modelled leaving the continuous covariates in their measurement scale. Simulations show that not accounting for possible dependence between registrations results in biased estimation of both the population size and standard error. The proposed method is applied to Dutch neural tube defect registration data.
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