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Spatial heterogeneity of type I error for local cluster detection tests
Aline Guttmann1, Xinran Li, Jean Gaudart
1Department of Biostatistics, Medical Informatics and Communication Technologies, Clermont University Hospital, Clermont-Ferrand F-63000, France. aline.guttmann@udamail.fr.
International Journal of Health Geographics
|June 3, 2014
Summary
Cluster detection tests (CDTs) show a spatial edge effect, with wrongly detected clusters (WDCs) more often centrally located. Careful consideration of edge clusters is needed in real-world analyses.
Area of Science:
- Spatial statistics
- Epidemiology
- Biostatistics
Background:
- Type I error in cluster detection tests (CDTs) requires spatial assessment.
- The spatial distribution of wrongly detected clusters (WDCs) is influenced by edge effects.
- CDTs detect and locate clusters, necessitating spatial evaluation of both power and error rates.
Purpose of the Study:
- To describe the spatial distribution of WDCs.
- To confirm and quantify the presence of edge effects in CDTs.
- To assess the spatial component of Type I error in cluster detection.
Main Methods:
- Simulated 40,000 datasets under null hypothesis of risk homogeneity.
- Utilized Kulldorff's spatial scan statistic for analysis.
- Defined participation rate per spatial unit to quantify edge effect.
Main Results:
- Type I error rate of 5% was maintained across simulations.
- A significant edge effect was observed, with WDCs more frequently found centrally.
- Participation rates showed a descending gradient from the center to the edge of the region.
Conclusions:
- Edge clusters in real data analyses warrant careful interpretation.
- WDCs are less likely to represent true clusters when located at the region's edge.
- Further research integrating power studies is recommended to optimize CDT performance.
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