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Spatial scan statistics with overdispersion
Author(s) -
Zhang Tonglin,
Zhang Zuoyi,
Lin Ge
Publication year - 2011
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4404
Subject(s) - overdispersion , poisson distribution , statistics , poisson regression , scan statistic , statistic , econometrics , mathematics , cluster (spacecraft) , computer science , count data , medicine , population , environmental health , programming language
The spatial scan statistic has been widely used in spatial disease surveillance and spatial cluster detection for more than a decade. However, overdispersion often presents in real‐world data, causing not only violation of the Poisson assumption but also excessive type I errors or false alarms. In order to account for overdispersion, we extend the Poisson‐based spatial scan test to a quasi‐Poisson‐based test. The simulation shows that the proposed method can substantially reduce type I error probabilities in the presence of overdispersion. In a case study of infant mortality in Jiangxi, China, both tests detect a cluster; however, a secondary cluster is identified by only the Poisson‐based test. It is recommended that a cluster detected by the Poisson‐based scan test should be interpreted with caution when it is not confirmed by the quasi‐Poisson‐based test. Copyright © 2011 John Wiley & Sons, Ltd.