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Estimating life expectancy in health and ill health by using a hidden Markov model

机译:通过使用隐马尔可夫模型估算健康和不良健康中的预期寿命

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摘要

Population studies with longitudinal follow-up and mortality information can be used to estimate transitions between healthy and unhealthy states before death. When health is defined with respect to cognitive ability during old age, the trajectory of performance is either static or downwards. The paper presents a hidden Markov model to describe the underlying categorized cognitive decline, where observed improvement of cognitive ability is modelled as misclassification. Maximum likelihood is used to estimate the transition intensities between the normal cognitive state, the cognitively impaired state and death. The methodology is extended to estimate total life expectancy and life expectancy with and without cognitive impairment. The paper presents estimates from the Medical Research Council cognitive function and ageing study that began in 1991 and where individuals have had up to eight interviews over the next 10 years. It is shown that the misclassification of the states is mainly caused by not detecting an impaired state. Individuals with more years of education have lower impaired life expectancies.
机译:具有纵向随访和死亡率信息的人群研究可用于估计死亡前健康状态与不健康状态之间的转换。如果在老年时根据认知能力来定义健康,则表现轨迹要么是静态的,要么是向下的。本文提出了一个隐马尔可夫模型来描述潜在的分类认知下降,其中观察到的认知能力提高被建模为错误分类。最大似然用于估计正常认知状态,认知障碍状态和死亡之间的过渡强度。扩展了该方法以估计总预期寿命和有或没有认知障碍的预期寿命。该论文提出了医学研究理事会的认知功能和衰老研究的评估结果,该研究始于1991年,在接下来的十年中,个人进行了多达八次访谈。结果表明,状态的错误分类主要是由于未检测到受损状态引起的。受过多年教育的人的预期寿命较低。

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