使用连续时间多状态模型估计预期寿命。
Estimation of life expectancies using continuous-time multi-state models.
机构信息
Department of Statistical Science, University College London Gower Street, London WC1E 6BT, UK.
University College London and University of Oxford, UK.
出版信息
Comput Methods Programs Biomed. 2019 Sep;178:11-18. doi: 10.1016/j.cmpb.2019.06.004. Epub 2019 Jun 5.
BACKGROUND AND OBJECTIVE
There is increasing interest in multi-state modelling of health-related stochastic processes. Given a fitted multi-state model with one death state, it is possible to estimate state-specific and marginal life expectancies. This paper introduces methods and new software for computing these expectancies.
METHODS
The definition of state-specific life expectancy given current age is an extension of mean survival in standard survival analysis. The computation involves the estimated parameters of a fitted multi-state model, and numerical integration. The new R package elect provides user-friendly functions to do the computation in the R software.
RESULTS
The estimation of life expectancies is explained and illustrated using the elect package. Functions are presented to explore the data, to estimate the life expectancies, and to present results.
CONCLUSIONS
State-specific life expectancies provide a communicable representation of health-related processes. The availability and explanation of the elect package will help researchers to compute life expectancies and to present their findings in an assessable way.
背景与目的
人们对健康相关随机过程的多状态建模越来越感兴趣。对于给定的带有一个死亡状态的拟合多状态模型，可以估计特定状态和边际预期寿命。本文介绍了计算这些预期寿命的方法和新软件。
方法
给定当前年龄的特定状态预期寿命的定义是标准生存分析中平均生存时间的扩展。计算涉及拟合多状态模型的估计参数和数值积分。新的 R 包 elect 提供了用户友好的函数，可在 R 软件中进行计算。
结果
使用 elect 包解释和说明预期寿命的估计。介绍了用于探索数据、估计预期寿命和呈现结果的功能。
结论
特定状态的预期寿命为健康相关过程提供了一种可交流的表示形式。elect 包的可用性和解释将帮助研究人员以可评估的方式计算预期寿命并呈现他们的发现。
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