Evaluation of spatial scan statistics for irregularly shaped clusters
Evaluation of spatial scan statistics for irregularly shaped clusters
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DOI：
10.1198/106186006x112396
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发表时间：
2006-06-01
影响因子：
2.4
通讯作者：
Huang, L
中科院分区：
文献类型：
--
作者：
Duczmal, L;Kulldorff, M;Huang, L
空间扫描统计通常用于地理疾病集群检测和评估。我们提出并实现了一个修改后的版本的模拟退火空间扫描统计，采用了“非紧凑性”的概念，以惩罚集群的形状非常不规则。我们评估其模拟退火扫描的功率，并将其与圆形和椭圆形空间扫描统计进行比较。我们观察到，与非紧性惩罚，模拟退火方法是具有竞争力的圆形和椭圆形扫描统计，都有很好的功率性能。椭圆扫描统计是计算速度更快，是非常适合轻度不规则的集群，但模拟退火方法更好地处理高度不规则的集群形状。新方法应用于美国东北部的乳腺癌死亡率数据。
Spatial scan statistics are commonly used for geographic disease cluster detection and evaluation. We propose and implement a modified version of the simulated annealing spatial scan statistic that incorporates the concept of "non-compactness" in order to penalize clusters that are very irregular in shape. We evaluate its power for the simulated annealing scan and compare it with the circular and elliptic spatial scan statistics. We observe that, with the non-compactness penalty, the simulated annealing method is competitive with the circular and elliptic scan statistic, and both have good power performance. The elliptic scan statistic is computationally faster and is well suited for mildly irregular clusters, but the simulated annealing method deals better with highly irregular cluster shapes. The new method is applied to breast cancer mortality data from northeastern United States.