Search results for "Scan statistic"

showing 4 items of 4 documents

Statistical methods for spatial cluster detection in childhood cancer incidence : A simulation study

2021

BACKGROUND AND OBJECTIVE: The potential existence of spatial clusters in childhood cancer incidence is a debated topic. Identification of such clusters may help to better understand etiology and develop preventive strategies. We evaluated widely used statistical approaches to cluster detection in this context.; METHODS: Incidence of newly diagnosed childhood cancer (140/1,000,000 children under 15 years) and nephroblastoma (7/1,000,000) was simulated. Clusters of defined size (1-50) were randomly assembled on the district level in Germany. Each cluster was simulated with different relative risk levels (1-100). For each combination 2000 iterations were done. Simulated data was then analyzed …

Cancer ResearchEpidemiologyScan statisticBayesian probabilityMedizinContext (language use)03 medical and health sciences0302 clinical medicineNeoplasmsStatisticsMedicineCluster AnalysisHumans030212 general & internal medicineSensitivity (control systems)Cluster analysisChildbusiness.industryIncidence (epidemiology)IncidenceIdentification (information)OncologyLaplace's method030220 oncology & carcinogenesisFemalebusiness
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Statistical Methods for the Geographical Analysis of Rare Diseases

2010

In this chapter we provide a summary of different methods for the detection of disease clusters. First of all, we give a summary of methods for computing estimates of the relative risk. These estimates provide smoothed values of the relative risks that can account for its spatial variation. Some methods for assessing spatial autocorrelation and general clustering are also discussed to test for significant spatial variation of the risk. In order to find the actual location of the clusters, scan methods are introduced. The spatial scan statistic is discussed as well as its extension by means of Generalised Linear Models that allows for the inclusion of covariates and cluster effects. In this …

Computer scienceScan statisticStatisticsCovariateLinear modelZero-inflated modelSpatial variabilityContext (language use)Cluster analysisSpatial analysis
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Methods of spatial cluster detection in rare childhood cancers: Benchmarking data and results from a simulation study on nephroblastoma

2021

Abstract The potential existence of spatial clusters in childhood cancer incidence is a debated topic. Identification of rare disease clusters in general may help to better understand disease etiology and develop preventive strategies against such entities. The incidence of newly diagnosed childhood malignancies under 15 years of age is 140/1,000,000. In this context, the subgroup of nephroblastoma represents an extremely rare entity with an annual incidence of 7/1,000,000. We evaluated widely used statistical approaches for spatial cluster detection in childhood cancer (Ref. [22] Schundeln et al., 2021, Cancer Epidemiology). For the simulation study, random high risk clusters of 1 to 50 ad…

Simulation studyComputer scienceScan statisticBayesian probabilityMedizinContext (language use)lcsh:Computer applications to medicine. Medical informaticsBayesian03 medical and health sciences0302 clinical medicineRandom distributionStatisticsCluster analysislcsh:Science (General)NephroblastomaData Article030304 developmental biology0303 health sciencesMultidisciplinaryBenchmarkingIdentification (information)Besag-NewellLaplace's methodSpatial clusterlcsh:R858-859.7Besag York MolliéRaw dataChildhood cancerSpatial scan statistic030217 neurology & neurosurgerylcsh:Q1-390Data in Brief
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Detection of spatial disease clusters with LISA functions.

2011

Detection of disease clusters is an important tool in epidemiology that can help to identify risk factors associated with the disease and in understanding its etiology. In this article we propose a method for the detection of spatial clusters where the locations of a set of cases and a set of controls are available. The method is based on local indicators of spatial association functions (LISA functions), particularly on the development of a local version of the product density, which is a second-order characteristic of spatial point processes. The behavior of the method is evaluated and compared with Kulldorff's spatial scan statistic by means of a simulation study. It is shown that the LI…

Statistics and ProbabilityAdultMaleDisease clustersEpidemiologyScan statisticIrregular shapePoint processDisease OutbreaksSet (abstract data type)StatisticsCluster AnalysisHumansComputer SimulationSensitivity (control systems)MathematicsAgedAged 80 and overbusiness.industryPattern recognitionMiddle AgedSpainData Interpretation StatisticalSpatial clusteringFemaleKidney DiseasesArtificial intelligencebusinessEpidemiologic MethodsType I and type II errorsStatistics in medicine
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