Evaluation and Estimation of the Provincial Infant Mortality Rate in China＇s Sixth Census

Objective To assess the data quality and estimate the provincial infant mortality rate（1q0） from China＇s sixth census. Methods A log-quadratic model is applied to under-fifteen data. We analyze and compare the average relative errors（AREs） for 1q0 between the estimated and reported values using the...

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Published in:生物医学与环境科学：英文版 2015, Vol.28 (6), p.410-420
Main Author: HU Song Bo WANG Fang YU Chuan Hua
Format: Article
Language:English
Subjects:
交叉验证法
人口普查
婴儿
平均相对误差
数据质量
死亡率
评价
评估
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creator HU Song Bo WANG Fang YU Chuan Hua
description Objective To assess the data quality and estimate the provincial infant mortality rate（1q0） from China＇s sixth census. Methods A log-quadratic model is applied to under-fifteen data. We analyze and compare the average relative errors（AREs） for 1q0 between the estimated and reported values using the leave-one-out cross-validation method. Results For the sixth census, the AREs are more than 100% for almost all provinces. The estimated average 1q0 level for 31 provinces is 12.3‰ for males and 10.7‰ for females. Conclusion The data for the provincial 1q0 from China＇s sixth census have a serious data quality problem. The actual levels of 1q0 for each province are significantly higher than the reported values.
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Methods A log-quadratic model is applied to under-fifteen data. We analyze and compare the average relative errors（AREs） for 1q0 between the estimated and reported values using the leave-one-out cross-validation method. Results For the sixth census, the AREs are more than 100% for almost all provinces. The estimated average 1q0 level for 31 provinces is 12.3‰ for males and 10.7‰ for females. Conclusion The data for the provincial 1q0 from China＇s sixth census have a serious data quality problem. 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Methods A log-quadratic model is applied to under-fifteen data. We analyze and compare the average relative errors（AREs） for 1q0 between the estimated and reported values using the leave-one-out cross-validation method. Results For the sixth census, the AREs are more than 100% for almost all provinces. The estimated average 1q0 level for 31 provinces is 12.3‰ for males and 10.7‰ for females. Conclusion The data for the provincial 1q0 from China＇s sixth census have a serious data quality problem. 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ispartof 生物医学与环境科学：英文版, 2015, Vol.28 (6), p.410-420
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2214-0190
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subjects 交叉验证法
人口普查
婴儿
平均相对误差
数据质量
死亡率
评价
评估
title Evaluation and Estimation of the Provincial Infant Mortality Rate in China＇s Sixth Census
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