Spatial Scan Statistics Adjusted for Multiple Clusters
Spatial Scan Statistics Adjusted for Multiple Clusters
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DOI：
10.1155/2010/642379
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发表时间：
2010-01-01
影响因子：
1.1
通讯作者：
Kulldorff, Martin
中科院分区：
文献类型：
--
作者：
Zhang, Zhenkui;Assuncao, Renato;Kulldorff, Martin
空间扫描统计是检验某一地理区域疾病聚集性的主要流行病学工具之一。虽然使用模型假设正确地评估了最有可能的集群的统计意义，但次级集群往往具有保守的高P值。在这篇文章中，我们提出了一种顺序版本的空间扫描统计量来调整研究区域中其他星团的存在。该过程通过顺序删除先前检测到的簇来消除由于更可能的簇对较不重要的簇的影响。在一项模拟研究中，我们利用美国东北部的地理和人口，计算了不同替代模型下关于真实星系团的位置和大小的I类错误概率和这种序贯检验的功率。结果表明，我们的方法的I类错误概率接近标称的a水平，对于二级星团，它的功率高于标准的未经调整的扫描统计量。
The spatial scan statistic is one of the main epidemiological tools to test for the presence of disease clusters in a geographical region. While the statistical significance of the most likely cluster is correctly assessed using the model assumptions, secondary clusters tend to have conservatively high P-values. In this paper, we propose a sequential version of the spatial scan statistic to adjust for the presence of other clusters in the study region. The procedure removes the effect due to the more likely clusters on less significant clusters by sequential deletion of the previously detected clusters. Using the Northeastern United States geography and population in a simulation study, we calculated the type I error probability and the power of this sequential test under different alternative models concerning the locations and sizes of the true clusters. The results show that the type I error probability of our method is close to the nominal a level and that for secondary clusters its power is higher than the standard unadjusted scan statistic.