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Performance map of a cluster detection test using extended power
- Source :
- International Journal of Health Geographics, International Journal of Health Geographics, BioMed Central, 2013, 12 (1), pp.47. ⟨10.1186/1476-072X-12-47⟩, International Journal of Health Geographics, 2013, 12 (1), pp.47. ⟨10.1186/1476-072X-12-47⟩
- Publication Year :
- 2013
- Publisher :
- HAL CCSD, 2013.
-
Abstract
- International audience; BACKGROUND: Conventional power studies possess limited ability to assess the performance of cluster detection tests. In particular, they cannot evaluate the accuracy of the cluster location, which is essential in such assessments. Furthermore, they usually estimate power for one or a few particular alternative hypotheses and thus cannot assess performance over an entire region. Takahashi and Tango developed the concept of extended power that indicates both the rate of null hypothesis rejection and the accuracy of the cluster location. We propose a systematic assessment method, using here extended power, to produce a map showing the performance of cluster detection tests over an entire region. METHODS: To explore the behavior of a cluster detection test on identical cluster types at any possible location, we successively applied four different spatial and epidemiological parameters. These parameters determined four cluster collections, each covering the entire study region. We simulated 1,000 datasets for each cluster and analyzed them with Kulldorff's spatial scan statistic. From the area under the extended power curve, we constructed a map for each parameter set showing the performance of the test across the entire region. RESULTS: Consistent with previous studies, the performance of the spatial scan statistic increased with the baseline incidence of disease, the size of the at-risk population and the strength of the cluster (i.e., the relative risk). Performance was heterogeneous, however, even for very similar clusters (i.e., similar with respect to the aforementioned factors), suggesting the influence of other factors. CONCLUSIONS: The area under the extended power curve is a single measure of performance and, although needing further exploration, it is suitable to conduct a systematic spatial evaluation of performance. The performance map we propose enables epidemiologists to assess cluster detection tests across an entire study region.
- Subjects :
- Extended power
Simulation study
Databases, Factual
General Computer Science
Scan statistic
Computer science
Alternative hypothesis
Business, Management and Accounting(all)
Population
Geographic Mapping
computer.software_genre
01 natural sciences
Power law
Congenital Abnormalities
Set (abstract data type)
010104 statistics & probability
03 medical and health sciences
Performance map
0302 clinical medicine
Cluster (physics)
Cluster Analysis
Humans
Registries
030212 general & internal medicine
0101 mathematics
education
education.field_of_study
Methodology
Public Health, Environmental and Occupational Health
General Business, Management and Accounting
Power (physics)
Cluster detection test
[SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie
Population Surveillance
[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie
France
Data mining
Null hypothesis
computer
Computer Science(all)
Subjects
Details
- Language :
- English
- ISSN :
- 1476072X
- Database :
- OpenAIRE
- Journal :
- International Journal of Health Geographics, International Journal of Health Geographics, BioMed Central, 2013, 12 (1), pp.47. ⟨10.1186/1476-072X-12-47⟩, International Journal of Health Geographics, 2013, 12 (1), pp.47. ⟨10.1186/1476-072X-12-47⟩
- Accession number :
- edsair.doi.dedup.....349212277ca3937f6570b8950759ac81