A class of multiplicity adjusted tests for spatial clustering based on case-control point data
A class of multiplicity adjusted tests for spatial clustering based on case-control point data
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DOI：
10.1111/j.1541-0420.2006.00633.x
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发表时间：
2007-03-01
期刊：
影响因子：
1.9
通讯作者：
Tango, Toshiro
中科院分区：
文献类型：
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作者：
Tango, Toshiro
提出了一类二次形式的测试，用于检测基于石油病例控制点数据的健康事件的空间聚类。它包括 Cuzick 和 Edwards 的检验统计量 (1990, Journal of the Royal Statistical Society, Series B 52, 73-104)。尽管他们使用了检验统计量的渐近正态性特性，但我们表明，对于中等大小的样本量，这种所有近似通常都很差。相反，我们建议使用中心卡方分布作为检验统计量渐近分布的更好近似。此外，不仅为了估计集群规模的未知参数的最佳值，而且为了通过改变参数值重复该过程来调整多次测试，我们提出了剖面 p 值的最小值！参数的检验统计量作为综合检验统计量。我们还提供统计数据来估计对显着聚类做出重大贡献的区域或案例。所提出的方法通过有关儿童白血病和淋巴瘤病例位置的数据集以及由受影响和未受影响的墓地组成的中世纪早期墓地位置的数据集进行说明。
A class of tests with quadratic forms for detecting spatial clustering of health events based oil case-control point data is proposed. it includes Cuzick and Edwards's test statistic (1990, Journal of the Royal Statistical Society, Series B 52, 73-104). Although they used the property of asymptotic normality of the test statistic, we show that such all approximation is generally poor for moderately large sample sizes. Instead, we suggest a central chi-square distribution as a better approximation to the asymptotic distribution of the test statistic. Furthermore, not only to estimate the optimal value of the unknown parameter oil the scale of cluster but also to adjust for multiple testing due to repeating the procedure by changing the parameter value, we propose the minimum, Of the profile p-value! of the test statistic for the parameter as an integrated test statistic. We also provide a statistic to estimate the areas or cases which make large contributions to significant clustering. The proposed methods are illustrated with a data set concerning the locations of cases of childhood leukemia and lymphoma and another on early medieval grave site locations consisting of affected and nonaffected grave sites.