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December 2007 Accounting for spatial correlation in the scan statistic
Ji Meng Loh, Zhengyuan Zhu
Ann. Appl. Stat. 1(2): 560-584 (December 2007). DOI: 10.1214/07-AOAS129

Abstract

The spatial scan statistic is widely used in epidemiology and medical studies as a tool to identify hotspots of diseases. The classical spatial scan statistic assumes the number of disease cases in different locations have independent Poisson distributions, while in practice the data may exhibit overdispersion and spatial correlation. In this work, we examine the behavior of the spatial scan statistic when overdispersion and spatial correlation are present, and propose a modified spatial scan statistic to account for that. Some theoretical results are provided to demonstrate that ignoring the overdispersion and spatial correlation leads to an increased rate of false positives, which is verified through a simulation study. Simulation studies also show that our modified procedure can substantially reduce the rate of false alarms. Two data examples involving brain cancer cases in New Mexico and chickenpox incidence data in France are used to illustrate the practical relevance of the modified procedure.

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Ji Meng Loh. Zhengyuan Zhu. "Accounting for spatial correlation in the scan statistic." Ann. Appl. Stat. 1 (2) 560 - 584, December 2007. https://doi.org/10.1214/07-AOAS129

Information

Published: December 2007
First available in Project Euclid: 30 November 2007

zbMATH: 1126.62107
MathSciNet: MR2415747
Digital Object Identifier: 10.1214/07-AOAS129

Keywords: Multiple comparisons , overdispersion , spatial correlation , spatial generalized linear mixed model , spatial scan statistic

Rights: Copyright © 2007 Institute of Mathematical Statistics

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Vol.1 • No. 2 • December 2007
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