ArticleInternational journal of health geographics2015
A nonparametric spatial scan statistic for continuous data.
Article in International journal of health geographics, 2015. 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.
- Optimizing the maximum reported cluster size in the spatial scan statistic for survival data.International journal of health geographics · 2021Article
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2 authors.
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Abstract
backgroundSpatial scan statistics are widely used for spatial cluster detection, and several parametric models exist. For continuous data, a normal-based scan statistic can be used. However, the performance of the model has not been fully evaluated for non-normal data.
methodsWe propose a nonparametric spatial scan statistic based on the Wilcoxon rank-sum test statistic and compared the performance of the method with parametric models via a simulation study under various scenarios.
resultsThe nonparametric method outperforms the normal-based scan statistic in terms of power and accuracy in almost all cases under consideration in the simulation study.
conclusionThe proposed nonparametric spatial scan statistic is therefore an excellent alternative to the normal model for continuous data and is especially useful for data following skewed or heavy-tailed distributions.
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