A scan statistic for continuous data based on the normal probability model

被引:186
作者
Kulldorff, Martin [1 ,2 ]
Huang, Lan [3 ]
Konty, Kevin [4 ]
机构
[1] Harvard Univ, Sch Med, Dept Populat Med, Boston, MA 02215 USA
[2] Harvard Pilgrim Hlth Care Inst, Boston, MA 02215 USA
[3] NCI, Bethesda, MD 20892 USA
[4] New York City Dept Hlth & Mental Hyg, New York, NY USA
关键词
INFANT-MORTALITY; CLUSTER DETECTION; SPATIAL-ANALYSIS; DISEASE; SURVEILLANCE; SEGREGATION; OUTBREAK; RISK;
D O I
10.1186/1476-072X-8-58
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
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.
引用
收藏
页数:9
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