ArticleInternational journal of health geographics2011
Data-driven inference for the spatial scan statistic.
Article in International journal of health geographics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- International society for disease surveillance conference 2011: building the future of public health surveillance.Emerging health threats journal · 2011Article
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Authors and funding
5 authors.
Funding
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Abstract
backgroundKulldorff's spatial scan statistic for aggregated area maps searches for clusters of cases without specifying their size (number of areas) or geographic location in advance. Their statistical significance is tested while adjusting for the multiple testing inherent in such a procedure. However, as is shown in this work, this adjustment is not done in an even manner for all possible cluster sizes.
resultsA modification is proposed to the usual inference test of the spatial scan statistic, incorporating additional information about the size of the most likely cluster found. A new interpretation of the results of the spatial scan statistic is done, posing a modified inference question: what is the probability that the null hypothesis is rejected for the original observed cases map with a most likely cluster of size k, taking into account only those most likely clusters of size k found under null hypothesis for comparison? This question is especially important when the p-value computed by the usual inference process is near the alpha significance level, regarding the correctness of the decision based in this inference.
conclusionsA practical procedure is provided to make more accurate inferences about the most likely cluster found by the spatial scan statistic.
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