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一种分段常数马尔可夫模型以及研究设计对健康和疾病状态下预期寿命估计的影响。

A piecewise-constant Markov model and the effects of study design on the estimation of life expectancies in health and ill health.

作者信息

van den Hout Ardo, Matthews Fiona E

机构信息

MRC Biostatistics Unit, Institute of Public Health Cambridge, UK.

出版信息

Stat Methods Med Res. 2009 Apr;18(2):145-62. doi: 10.1177/0962280208089090. Epub 2008 Apr 29.

Abstract

Multi-state models are frequently applied to describe transitions over time between three states: healthy, not healthy and death. The three-state model can be used to estimate life expectancies in health and ill health. In this article, continuous-time Markov models are specified for the transitions between the three states. Transition intensities are regressed on age as a time-dependent covariate. The covariate is handled in a piecewise-constant fashion where the time interval between two consecutive observations is divided into subintervals of fixed and equal lengths. Study design choices such as sample size, length of follow-up, and time intervals between observations are investigated in a simulation study. The effects on parameter estimation are discussed as well as the effects on the estimation of life expectancies. In addition, data taken from the UK Cognitive Functioning and Ageing Study are analysed.

摘要

多状态模型经常被用于描述随时间在三种状态之间的转变

健康、非健康和死亡。三状态模型可用于估计健康和不健康状态下的预期寿命。在本文中,针对这三种状态之间的转变指定了连续时间马尔可夫模型。将转移强度作为时间依存协变量对年龄进行回归分析。协变量以分段常数的方式处理,即两个连续观测值之间的时间间隔被划分为固定且等长的子区间。在一项模拟研究中考察了诸如样本量、随访时长以及观测值之间的时间间隔等研究设计选择。讨论了其对参数估计的影响以及对预期寿命估计的影响。此外,还分析了取自英国认知功能与老龄化研究的数据。

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