Cited 14 times in
A nonparametric spatial scan statistic for continuous data
DC Field | Value | Language |
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dc.contributor.author | 정인경 | - |
dc.date.accessioned | 2016-02-04T11:59:33Z | - |
dc.date.available | 2016-02-04T11:59:33Z | - |
dc.date.issued | 2015 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/141651 | - |
dc.description.abstract | BACKGROUND: Spatial scan statistics are widely used for spatial cluster detection, and several parametric models exist. For continuous data, a normal-based scan statistic can be used. However, the performance of the model has not been fully evaluated for non-normal data. METHODS: We propose a nonparametric spatial scan statistic based on the Wilcoxon rank-sum test statistic and compared the performance of the method with parametric models via a simulation study under various scenarios. RESULTS: The nonparametric method outperforms the normal-based scan statistic in terms of power and accuracy in almost all cases under consideration in the simulation study. CONCLUSION: The proposed nonparametric spatial scan statistic is therefore an excellent alternative to the normal model for continuous data and is especially useful for data following skewed or heavy-tailed distributions. | - |
dc.description.statementOfResponsibility | open | - |
dc.format.extent | 30 | - |
dc.relation.isPartOf | INTERNATIONAL JOURNAL OF HEALTH GEOGRAPHICS | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/2.0/kr/ | - |
dc.subject.MESH | Cluster Analysis | - |
dc.subject.MESH | Geographic Mapping* | - |
dc.subject.MESH | Humans | - |
dc.subject.MESH | Models, Statistical | - |
dc.subject.MESH | Population Surveillance/methods* | - |
dc.subject.MESH | Statistics, Nonparametric* | - |
dc.title | A nonparametric spatial scan statistic for continuous data | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Biostatistics (의학통계학) | - |
dc.contributor.googleauthor | Inkyung Jung | - |
dc.contributor.googleauthor | Ho Jin Cho | - |
dc.identifier.doi | 10.1186/s12942-015-0024-6 | - |
dc.admin.author | false | - |
dc.admin.mapping | false | - |
dc.contributor.localId | A03693 | - |
dc.relation.journalcode | J01119 | - |
dc.identifier.eissn | 1476-072X | - |
dc.identifier.pmid | 26481724 | - |
dc.subject.keyword | Spatial cluster detection test | - |
dc.subject.keyword | Normal-based scan statistic | - |
dc.subject.keyword | Wilcoxon rank-sum test | - |
dc.contributor.alternativeName | Jung, In Kyung | - |
dc.contributor.affiliatedAuthor | Jung, In Kyung | - |
dc.rights.accessRights | free | - |
dc.citation.volume | 14 | - |
dc.citation.startPage | 30 | - |
dc.identifier.bibliographicCitation | INTERNATIONAL JOURNAL OF HEALTH GEOGRAPHICS, Vol.14 : 30, 2015 | - |
dc.identifier.rimsid | 30792 | - |
dc.type.rims | ART | - |
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