International Journal of Health Geographics Open Access a Scan Statistic for Continuous Data Based on the Normal Probability Model
International Journal of Health Geographics Open Access a Scan Statistic for Continuous Data Based on the Normal Probability Model
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影响因子：
8.6
通讯作者：
M. Kulldorff;Lan Huang;K. Konty
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作者：
M. Kulldorff;Lan Huang;K. Konty
时间、空间和时空扫描统计通常用于检测和评估时间和/或地理疾病群组的统计意义，而不需要关于这些群组的位置、时间段或大小的任何预先假设。扫描统计数据主要用于计数数据，如发病率或死亡率。有时，人们有兴趣寻找与一个连续变量相关的集群，例如儿童的铅水平或低出生体重。对于这样的连续数据，我们提出了一种扫描统计量，其中似然性是使用正态概率模型来计算的。它还可以用于其他发行版，同时仍然保持正确的阿尔法级别。在新方法的应用中，我们在纽约市寻找低出生体重的地理集群。
Temporal, spatial and space-time scan statistics are commonly used to detect and evaluate the statistical significance of temporal and/or geographical disease clusters, without any prior assumptions on the location, time period or size of those clusters. Scan statistics are mostly used for count data, such as disease incidence or mortality. Sometimes there is an interest in looking for clusters with respect to a continuous variable, such as lead levels in children or low birth weight. For such continuous data, we present a scan statistic where the likelihood is calculated using the the normal probability model. It may also be used for other distributions, while still maintaining the correct alpha level. In an application of the new method, we look for geographical clusters of low birth weight in New York City.