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Mortality incidence estimation using federal death certificate and natality data with an application to Tay-Sachs disease

机译:使用联邦死亡证明和出生数据估算死亡率,并将其应用于Tay-Sachs病

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For confidentiality reasons, US federal death certificate data are incomplete with regards to the dates of birth and death for the decedents, making calculation of total lifetime of a decedent impossible and thus estimation of mortality incidence difficult. This paper proposes the use of natality data and an imputation-based method to estimate age-specific mortality incidence rates in the face of this missing information. By utilizing previously determined probabilities of birth, a birth date and death date are imputed for every decedent in the dataset. Thus, the birth cohort of each individual is imputed, and the total on-study time can be calculated. This idea is implemented in two approaches for estimation of mortality incidence rates. The first is an extension of a person-time approach, while the second is an extension of a life table approach. Monte Carlo simulations showed that both approaches perform well in comparison to the ideal complete data methods, but that the person-time method is preferred. An application to Tay-Sachs disease is demonstrated. It is concluded that the imputation methods proposed provide valid estimates of the incidence of death from death certificate data without the need for additional assumptions under which usual mortality rates provide valid estimates.
机译:出于保密原因,关于死者的出生日期和死亡日期,美国联邦死亡证书数据不完整,因此无法计算死者的总寿命,因此很难估计死亡率。本文提出了使用出生数据和一种基于归因的方法来估计面对这种缺失信息的特定年龄死亡率的发生率。通过利用先前确定的出生概率,可以为数据集中的每个后代估算出生日期和死亡日期。因此,可以估算出每个人的出生队列,并且可以计算出总的学习时间。这个想法可以通过两种方法来估计死亡率。第一个是人员时间方法的扩展,而第二个是生命表方法的扩展。蒙特卡洛模拟显示,与理想的完整数据方法相比,这两种方法都具有良好的性能,但首选个人时间方法。证明了其可用于Tay-Sachs病。结论是,提出的估算方法可以从死亡证明数据中提供死亡发生率的有效估计,而无需其他假设,常规死亡率可以提供有效估计。

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