Am J Epidemiol. 2023 Aug 4;192(8):1396-1405. doi: 10.1093/aje/kwad073.
The purpose of this study was to assess the precision, uncertainty, and normality of small-area life expectancy estimates calculated using Bayesian spatiotemporal models. We hypothesized 6 scenarios in which all 247 districts of South Korea had the same year-specific female population of 500, 1,000, 2,000, 5,000, 10,000, and 25,000 individuals during the study period (2013-2017). We generated 1,000 hypothetical data sets for each scenario and calculated district-year life expectancies. The precision and uncertainty of life expectancy estimates were compared between 2 Bayesian spatiotemporal models and the traditional method and Bayesian spatial models. We examined the normality of the life expectancy distributions generated by each method and investigated an optimal cutoff value for the comparisons. The Bayesian spatiotemporal models produced precise life expectancy estimates. However, the 95% uncertainty interval contained the true value with a probability of less than 95%. The Bayesian spatiotemporal models violated the normality assumption in scenarios with small population sizes. Therefore, life expectancy comparisons should be conducted using a cutoff value that minimizes false-positive and false-negative rates. We propose 0.8 as a cutoff value for determining the statistical significance of the difference in life expectancy.
本研究旨在评估使用贝叶斯时空模型计算的小区域预期寿命估计的精度、不确定性和正态性。我们假设了 6 种情况，在这 6 种情况下，韩国的 247 个地区在研究期间（2013-2017 年）都具有相同的特定年份女性人口，分别为 500、1000、2000、5000、10000 和 25000 人。我们为每个场景生成了 1000 个假设数据集，并计算了地区-年份的预期寿命。比较了两种贝叶斯时空模型与传统方法和贝叶斯空间模型之间的预期寿命估计的精度和不确定性。我们检验了每种方法生成的预期寿命分布的正态性，并研究了比较的最佳截断值。贝叶斯时空模型产生了精确的预期寿命估计。然而，95%的置信区间包含真实值的概率小于 95%。在人口规模较小的情况下，贝叶斯时空模型违反了正态性假设。因此，应该使用最小化假阳性和假阴性率的截断值来进行预期寿命比较。我们建议 0.8 作为确定预期寿命差异的统计学显著性的截断值。
