Scale and shape issues in focused cluster power for count data.
Scale and shape issues in focused cluster power for count data.
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DOI：
10.1186/1476-072x-4-8
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发表时间：
2005-03-31
影响因子：
4.9
通讯作者：
Hebert JR
中科院分区：
文献类型：
--
作者：
Puett RC;Lawson AB;Clark AB;Aldrich TE;Porter DE;Feigley CE;Hebert JR
近年来，对疾病群检测的统计方法的发展的兴趣经历了快速增长。统计功效的评估为环境相关疾病集群调查中选择合适的统计方法提供了重要信息。已发表的功效评估尚未解决使用模型进行集中聚类检测的问题，也未充分调查疾病聚类规模和形状的问题。由于气象和其他因素会影响环境毒物的扩散，因此，环境接触和相关疾病会以各种空间模式扩散。这项研究模拟了一个位于中心的单一污染源周围的各种形状和规模的疾病集群。我们评估了一系列集中的聚类测试和广义线性模型的能力，以检测这些不同的聚类形状和规模的计数数据。一般来说，当测试或模型包括特定于被检查的聚类形状的参数时，检测聚焦聚类的假设测试和模型的能力得到提高（即，包括用于方向的函数，提高了模型检测具有角度效应的聚类的能力）。然而，检测风险达到峰值然后下降的集群的能力有限。这项调查的结果显示，根据集群的规模和形状以及所应用的测试或模型，功率发生了相当大的变化。这些研究结果表明，选择一个测试或模型的功能，适合检测疾病集群的空间模式的重要性。
Interest in the development of statistical methods for disease cluster detection has experienced rapid growth in recent years. Evaluations of statistical power provide important information for the selection of an appropriate statistical method in environmentally-related disease cluster investigations. Published power evaluations have not yet addressed the use of models for focused cluster detection and have not fully investigated the issues of disease cluster scale and shape. As meteorological and other factors can impact the dispersion of environmental toxicants, it follows that environmental exposures and associated diseases can be dispersed in a variety of spatial patterns. This study simulates disease clusters in a variety of shapes and scales around a centrally located single pollution source. We evaluate the power of a range of focused cluster tests and generalized linear models to detect these various cluster shapes and scales for count data. In general, the power of hypothesis tests and models to detect focused clusters improved when the test or model included parameters specific to the shape of cluster being examined (i.e. inclusion of a function for direction improved power of models to detect clustering with an angular effect). However, power to detect clusters where the risk peaked and then declined was limited. Findings from this investigation show sizeable changes in power according to the scale and shape of the cluster and the test or model applied. These findings demonstrate the importance of selecting a test or model with functions appropriate to detect the spatial pattern of the disease cluster.