Gumbel based p-value approximations for spatial scan statistics

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چکیده

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Gumbel based p-value approximations for spatial scan statistics

BACKGROUND The spatial and space-time scan statistics are commonly applied for the detection of geographical disease clusters. Monte Carlo hypothesis testing is typically used to test whether the geographical clusters are statistically significant as there is no known way to calculate the null distribution analytically. In Monte Carlo hypothesis testing, simulated random data are generated mult...

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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-Pois...

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Spatial Scan Statistics Adjusted for Multiple Clusters

The spatial scan statistic is one of the main epidemiological tools to test for the presence of disease clusters in a geographical region. While the statistical significance of the most likely cluster is correctly assessed using the model assumptions, secondary clusters tend to have conservatively high P-values. In this paper, we propose a sequential version of the spatial scan statistic to adj...

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ژورنال

عنوان ژورنال: International Journal of Health Geographics

سال: 2010

ISSN: 1476-072X

DOI: 10.1186/1476-072x-9-61