空间经验贝叶斯平滑法在肺癌死亡空间分析中的应用  

The Application of Spatial Empirical Bayesian Smoothing Method in the Spatial Analysis of Lung Cancer Mortality

作　　者：李迎迎[1] 孟郁洁[1] 夏兰芳[1] 陈倩倩[1] 戚晓鹏[1] 马家奇[1] 

机构地区：[1]中国疾病预防控制中心公共卫生监测与信息服务中心

出　　处：《中国数字医学》2014年第3期104-106,共3页China Digital Medicine

基　　金：国家重大科学研究计划资助(编号:2012CB955504)~~

摘　　要：目的:探讨空间经验贝叶斯平滑法在肺癌死亡空间分析中的应用。方法:利用2010年研究区死亡监测资料,采用空间经验贝叶斯平滑法和地理信息技术分析肺癌死亡的空间分布特征。结果:平滑后肺癌死亡的插值格网图显示,死亡率向局部均值靠拢,高低值区域分布集中,聚集趋势明显。结论:空间经验贝叶斯平滑对肺癌死亡率的估计更加稳定,可为小人群死亡率的空间特征分析提供一种有效的研究方法。Objective： To explore the application of spatial empirical bayesian smoothing methods in spatial analysis of lung cancer mortality. Methods： To analyze the spatial distribution characteristics of tung cancer mortality by using spatial empirical bayesian smoothing methods and geographic information systems based on death surveillance data of the research area in 2010. Results： The interpolation grid map of lung cancer mortality rates was showing that mortality rates were close to the local average values, the distribution of high and low values presenting spatial cluster phenomenon after Smoothing. Conclusion： Spatial empirical bayesian smoothing methods were explored by making the estimate of lung cancer mortality more stable, providing an effective research method for spatial analysis of the mortality rates of small population.

关 键 词：肺癌 死亡率 空间经验贝叶斯平滑 

分 类 号：R734.2[医药卫生—肿瘤] P951[医药卫生—临床医学]