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qlifetable:一个用于构建季度生命表的R软件包。

qlifetable: An R package for constructing quarterly life tables.

作者信息

Pavía Jose M, Lledó Josep

机构信息

Universitat de Valencia, Valencia, Spain.

出版信息

PLoS One. 2025 Feb 21;20(2):e0315937. doi: 10.1371/journal.pone.0315937. eCollection 2025.

Abstract

The big data revolution has greatly expanded the availability of microdata on vital statistics, providing researchers with unprecedented access to large and complex datasets on birth, death, migration, and population, sometimes even including exact dates of demographic events. This has led to the development of a novel methodology for estimating sub-annual life tables that offers new opportunities for the insurance industry, also potentially impacting on the management of pension funds and social security systems. This paper introduces the qlifetable package, an R implementation of this methodology. It begins by detailing how basic summary statistics are computed by the package from detailed individual records, including the length of age years, which should be observed as relative (subjective) to ensure congruency between age and calendar time when measuring exposure times and exact ages of individuals at events. This is a new result that compels the observation of time as relative in the disciplines of actuarial science, risk management and demography. Afterwards, the paper demonstrates the use of the package, which integrates a set of functions for estimating crude quarterly (and annual) death rates, calculating seasonal-ageing indexes (SAIs) and building quarterly life tables for a (general or insured) population by exploiting either microdata of dates of births and events or summary statistics.

摘要

大数据革命极大地扩展了生命统计微观数据的可得性,为研究人员提供了前所未有的机会,使其能够获取关于出生、死亡、迁移和人口的大型复杂数据集,有时甚至包括人口事件的确切日期。这催生了一种用于估计年度以下生命表的新方法,为保险业带来了新机遇,也可能对养老基金和社会保障系统的管理产生影响。本文介绍了qlifetable软件包,它是该方法的R语言实现。文章首先详细说明了该软件包如何根据详细的个人记录计算基本汇总统计量,包括年龄年数的长度,在测量暴露时间和事件发生时个人的确切年龄时,应将其视为相对的(主观的),以确保年龄与日历时间的一致性。这是一个新成果,促使精算科学、风险管理和人口统计学领域将时间视为相对的。之后,本文展示了该软件包的使用方法,它集成了一组函数,可通过利用出生日期和事件的微观数据或汇总统计量来估计季度(和年度)粗死亡率、计算季节性老化指数(SAI)以及为(一般或参保)人群构建季度生命表。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee31/11845031/f1bd93217fa0/pone.0315937.g001.jpg

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