Spatial Scan Statistics Adjusted for Multiple Clusters
Joint Authors
Assunção, Renato
Zhang, Zhenkui
Kulldorff, Martin
Source
Journal of Probability and Statistics
Issue
Vol. 2010, Issue 2010 (31 Dec. 2010), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2010-08-30
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
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 adjust for the presence of other clusters in the study region.
The procedure removes the effect due to the more likely clusters on less significant clusters by sequential deletion of the previously detected clusters.
Using the Northeastern United States geography and population in a simulation study, we calculated the type I error probability and the power of this sequential test under different alternative models concerning the locations and sizes of the true clusters.
The results show that the type I error probability of our method is close to the nominal α level and that for secondary clusters its power is higher than the standard unadjusted scan statistic.
American Psychological Association (APA)
Zhang, Zhenkui& Assunção, Renato& Kulldorff, Martin. 2010. Spatial Scan Statistics Adjusted for Multiple Clusters. Journal of Probability and Statistics،Vol. 2010, no. 2010, pp.1-11.
https://search.emarefa.net/detail/BIM-487583
Modern Language Association (MLA)
Zhang, Zhenkui…[et al.]. Spatial Scan Statistics Adjusted for Multiple Clusters. Journal of Probability and Statistics No. 2010 (2010), pp.1-11.
https://search.emarefa.net/detail/BIM-487583
American Medical Association (AMA)
Zhang, Zhenkui& Assunção, Renato& Kulldorff, Martin. Spatial Scan Statistics Adjusted for Multiple Clusters. Journal of Probability and Statistics. 2010. Vol. 2010, no. 2010, pp.1-11.
https://search.emarefa.net/detail/BIM-487583
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-487583