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dc.contributor.authorSong, Changhong
dc.contributor.authorKulldorff, Martin
dc.date.accessioned2011-03-16T14:31:34Z
dc.date.issued2003
dc.identifier.citationSong, Changhong, and Martin Kulldorff. 2003. Power evaluation of disease clustering tests. International Journal of Health Geographics 2:9.en_US
dc.identifier.issn1476-072Xen_US
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:4742716
dc.description.abstractBackground: Many different test statistics have been proposed to test for spatial clustering. Some of these statistics have been widely used in various applications. In this paper, we use an existing collection of 1,220,000 simulated benchmark data, generated under 51 different clustering models, to compare the statistical power of several disease clustering tests. These tests are Besag-Newell's R, Cuzick-Edwards' k-Nearest Neighbors (k-NN), the spatial scan statistic, Tango's Maximized Excess Events Test (MEET), Swartz' entropy test, Whittemore's test, Moran's I and a modification of Moran's I. Results: Except for Moran's I and Whittemore's test, all other tests have good power for detecting some kind of clustering. The spatial scan statistic is good at detecting localized clusters. Tango's MEET is good at detecting global clustering. With appropriate choice of parameter, Besag-Newell's R and Cuzick-Edwards' k-NN also perform well. Conclusion: The power varies greatly for different test statistics and alternative clustering models. Consideration of the power is important before we decide which test statistic to use.en_US
dc.language.isoen_USen_US
dc.publisherBioMed Centralen_US
dc.relation.isversionofdoi:10.1186/1476-072X-2-9en_US
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC333429/pdf/en_US
dash.licenseLAA
dc.subjectbenchmark dataen_US
dc.subjectpoweren_US
dc.subjectcluster detectionen_US
dc.subjecthot spot clustersen_US
dc.subjectglobal chain clusteringen_US
dc.subjecttest for spatial randomnessen_US
dc.subjectspatial statisticsen_US
dc.titlePower Evaluation of Disease Clustering Testsen_US
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden_US
dc.relation.journalInternational Journal of Health Geographicsen_US
dash.depositing.authorKulldorff, Martin
dc.date.available2011-03-16T14:31:34Z
dash.affiliation.otherHMS^Population Medicineen_US
dc.identifier.doi10.1186/1476-072X-2-9*
dash.contributor.affiliatedKulldorff, Martin


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