在晚期癌症发病率的地理统计绘图中结合基于区域和个体层面的数据。
Combining area-based and individual-level data in the geostatistical mapping of late-stage cancer incidence.
作者信息
Goovaerts Pierre
机构信息
BioMedware, Inc., Ann Arbor, MI 48104, USA.
出版信息
Spat Spatiotemporal Epidemiol. 2009 Oct-Dec;1(1):61-71. doi: 10.1016/j.sste.2009.07.001.
Abstract
This paper presents a geostatistical approach to incorporate individual-level data (e.g. patient residences) and area-based data (e.g. rates recorded at census tract level) into the mapping of late-stage cancer incidence, with an application to breast cancer in three Michigan counties. Spatial trends in cancer incidence are first estimated from census data using area-to-point binomial kriging. This prior model is then updated using indicator kriging and individual-level data. Simulation studies demonstrate the benefits of this two-step approach over methods (kernel density estimation and indicator kriging) that process only residence data.
摘要
本文提出了一种地质统计学方法，将个体层面的数据（如患者居住地）和基于区域的数据（如普查区层面记录的发病率）纳入晚期癌症发病率的地图绘制中，并应用于密歇根州的三个县的乳腺癌研究。首先使用面积到点的二项式克里金法从普查数据中估计癌症发病率的空间趋势。然后使用指示克里金法和个体层面的数据对这个先验模型进行更新。模拟研究表明，与仅处理居住数据的方法（核密度估计和指示克里金法）相比，这种两步法具有优势。
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