带奖励的马尔可夫链离散多态生命表的柔性过渡时序。

IF 1.5 Q2 DEMOGRAPHY
D. Schneider, M. Myrskylä, Alyson A. van Raalte
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引用次数: 4

摘要

离散时间多状态生命表很有吸引力,因为与连续时间生命表相比,它们更容易理解和应用。虽然这样的模型是基于离散时间网格的,但在假设过渡发生在其他时间(如中期)的情况下,计算派生的幅度(例如国家占用时间)通常是有用的。不幸的是,目前可用的模型只允许很少的转换时间选择。我们建议使用带奖励的马尔可夫链作为将过渡时间信息纳入模型的一般方法。我们通过使用不同的退休过渡时间估计工作预期寿命来说明基于奖励的多状态生命表的有用性。我们还证明了对于单状态情况,奖励方法与传统的生命表方法完全匹配。最后,我们提供了复制论文中所有结果的代码,以及R和Stata包,用于所提出方法的一般使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Flexible transition timing in discrete-time multistate life tables using Markov chains with rewards.
Discrete-time multistate life tables are attractive because they are easier to understand and apply in comparison with their continuous-time counterparts. While such models are based on a discrete time grid, it is often useful to calculate derived magnitudes (e.g. state occupation times), under assumptions which posit that transitions take place at other times, such as mid-period. Unfortunately, currently available models allow very few choices about transition timing. We propose the use of Markov chains with rewards as a general way of incorporating information on the timing of transitions into the model. We illustrate the usefulness of rewards-based multistate life tables by estimating working life expectancies using different retirement transition timings. We also demonstrate that for the single-state case, the rewards approach matches traditional life-table methods exactly. Finally, we provide code to replicate all results from the paper plus R and Stata packages for general use of the method proposed.
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来源期刊
CiteScore
1.80
自引率
0.00%
发文量
15
审稿时长
26 weeks
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