Daniel C Schneider, Mikko Myrskylä, Alyson van Raalte
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引用次数: 0
摘要
离散时间多态生命表具有吸引力,因为与连续时间生命表相比,它们更容易理解和应用。虽然此类模型基于离散时间网格,但在假设过渡发生在其他时间(如周期中期)的情况下,计算推导出的量级(如状态占据时间)往往很有用。遗憾的是,目前可用的模型很少允许选择过渡时间。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算工作预期寿命,说明了基于奖励的多态生命表的实用性。我们还证明,在单州情况下,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 软件包,以便普遍使用所提出的方法。
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.
期刊介绍:
For over half a century, Population Studies has reported significant advances in methods of demographic analysis, conceptual and mathematical theories of demographic dynamics and behaviour, and the use of these theories and methods to extend scientific knowledge and to inform policy and practice. The Journal"s coverage of this field is comprehensive: applications in developed and developing countries; historical and contemporary studies; quantitative and qualitative studies; analytical essays and reviews. The subjects of papers range from classical concerns, such as the determinants and consequences of population change, to such topics as family demography and evolutionary and genetic influences on demographic behaviour.