ArticlePloS one2016
Selection of the Maximum Spatial Cluster Size of the Spatial Scan Statistic by Using the Maximum Clustering Set-Proportion Statistic.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed.
- Integrating disease mapping and flexible scan statistics to identify and visualize spatial clusters.PloS one · 2026Article
- The use of SatScan software to map spatiotemporal trends and detect disease clusters: a systematic review.Communications medicine · 2025Article
- Spatial distribution and associated factors of cesarean section in Ethiopia using mini EDHS 2019 data: a community based cross-sectional study.Scientific reports · 2024Article
- Optimizing the maximum reported cluster size for the multinomial-based spatial scan statistic.International journal of health geographics · 2023Article
- Reclaiming independence in spatial-clustering datasets: A series of data-driven spatial weights matrices.Statistics in medicine · 2022Article
- Spatiotemporal trends and socioecological factors associated with Lyme disease in eastern Ontario, Canada from 2010-2017.BMC public health · 2022Article
- Detection of temporal, spatial and spatiotemporal clustering of malaria incidence in northwest Ethiopia, 2012-2020.Scientific reports · 2022Article
- Spatiotemporal cluster patterns of hand, foot, and mouth disease at the province level in mainland China, 2011-2018.PloS one · 2022Article
- Spatial inequality, characteristics of internal migration, and pulmonary tuberculosis in China, 2011-2017: a spatial analysis.Infectious diseases of poverty · 2020Article
- Using the maximum clustering heterogeneous set-proportion to select the maximum window size for the spatial scan statistic.Scientific reports · 2020Article
- Spatial pattern of perinatal mortality and its determinants in Ethiopia: Data from Ethiopian Demographic and Health Survey 2016.PloS one · 2020Article
- Spatial and temporal clustering analysis of tuberculosis in the mainland of China at the prefecture level, 2005-2015.Infectious diseases of poverty · 2018Article
- Using the Kulldorff's scan statistical analysis to detect spatio-temporal clusters of tuberculosis in Qinghai Province, China, 2009-2016.BMC infectious diseases · 2017Article
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5 authors.
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Abstract
Spatial scan statistics are widely used in various fields. The performance of these statistics is influenced by parameters, such as maximum spatial cluster size, and can be improved by parameter selection using performance measures. Current performance measures are based on the presence of clusters and are thus inapplicable to data sets without known clusters. In this work, we propose a novel overall performance measure called maximum clustering set-proportion (MCS-P), which is based on the likelihood of the union of detected clusters and the applied dataset. MCS-P was compared with existing performance measures in a simulation study to select the maximum spatial cluster size. Results of other performance measures, such as sensitivity and misclassification, suggest that the spatial scan statistic achieves accurate results in most scenarios with the maximum spatial cluster sizes selected using MCS-P. Given that previously known clusters are not required in the proposed strategy, selection of the optimal maximum cluster size with MCS-P can improve the performance of the scan statistic in applications without identified clusters.
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