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基于年龄的两性人口贝叶斯重建:估计出生时的性别比和死亡率性别比。

Bayesian Reconstruction of Two-Sex Populations by Age: Estimating Sex Ratios at Birth and Sex Ratios of Mortality.

作者信息

Wheldon Mark C, Raftery Adrian E, Clark Samuel J, Gerland Patrick

机构信息

Auckland University of Technology.

University of Washington.

出版信息

J R Stat Soc Ser A Stat Soc. 2015 Oct;178(4):977-1007. doi: 10.1111/rssa.12104. Epub 2015 Feb 12.

DOI:10.1111/rssa.12104
PMID:26612972
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4657758/
Abstract

The original version of Bayesian reconstruction, a method for estimating age-specific fertility, mortality, migration and population counts of the recent past with uncertainty, produced estimates for female-only populations. Here we show how two-sex populations can be similarly reconstructed and probabilistic estimates of various sex ratio quantities obtained. We demonstrate the method by reconstructing the populations of India from 1971 to 2001, Thailand from 1960 to 2000, and Laos from 1985 to 2005. We found evidence that in India, sex ratio at birth exceeded its conventional upper limit of 1.06, and, further, increased over the period of study, with posterior probability above 0.9. In addition, almost uniquely, we found evidence that life expectancy at birth () was lower for females than for males in India (posterior probability for 1971-1976 equal to 0.79), although there was strong evidence for a narrowing of the gap through to 2001. In both Thailand and Laos, we found strong evidence for the more usual result that was greater for females and, in Thailand, that the difference increased over the period of study.

摘要

贝叶斯重建的原始版本是一种用于估计近期特定年龄生育率、死亡率、迁移率和人口数量并带有不确定性的方法,该方法仅针对女性人口进行估计。在此,我们展示如何对两性人口进行类似的重建,并获得各种性别比数量的概率估计。我们通过重建1971年至2001年的印度人口、1960年至2000年的泰国人口以及1985年至2005年的老挝人口来演示该方法。我们发现有证据表明,在印度,出生性别比超过了其传统上限1.06,并且在研究期间进一步上升,后验概率超过0.9。此外,几乎独一无二的是,我们发现有证据表明,在印度,出生时预期寿命()女性低于男性(1971年至1976年的后验概率等于0.79),尽管有强有力的证据表明到2001年差距在缩小。在泰国和老挝,我们发现有强有力的证据支持更常见的结果,即女性的预期寿命更长,并且在泰国,这种差异在研究期间有所增加。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35f/5008419/47b74ca5df4f/RSSA-178-977-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35f/5008419/2d1d0904b851/RSSA-178-977-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35f/5008419/2ebcd0d8eac9/RSSA-178-977-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35f/5008419/fba135d05379/RSSA-178-977-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35f/5008419/d3ab44138eb9/RSSA-178-977-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35f/5008419/26c196a0b5f7/RSSA-178-977-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35f/5008419/ecbd028b623b/RSSA-178-977-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35f/5008419/47b74ca5df4f/RSSA-178-977-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35f/5008419/2d1d0904b851/RSSA-178-977-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35f/5008419/2ebcd0d8eac9/RSSA-178-977-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35f/5008419/fba135d05379/RSSA-178-977-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35f/5008419/d3ab44138eb9/RSSA-178-977-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35f/5008419/26c196a0b5f7/RSSA-178-977-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35f/5008419/ecbd028b623b/RSSA-178-977-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35f/5008419/47b74ca5df4f/RSSA-178-977-g007.jpg

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Bayesian Population Projections for the United Nations.联合国的贝叶斯人口预测
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