Statistical detection and surveillance of geographic clusters

목차 (Table of Contents)

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• Introduction and OverviewSetting the StageThe Roles of Spatial Statistics in Public Health and Other FieldsLimitations Associated with the Visualization of Spatial DataSome Fundamental Concepts and DistinctionsTypes of Tests for ClusteringStructure of the BookSoftware Resources and Sample DataIntroductory Spatial Statistics: Description and InferenceIntroductionMean CenterMedian CenterStandard DistanceRelative Standard DistanceInferential Statistical Tests of Central Tendency and DispersionIllustrationAngular DataCharacteristics of Spatial Processes: First-Order and Second-Order VariationKernel Density EstimationK-FunctionsDifferences and Ratios of Kernel Density EstimatorsDifferences in K-FunctionsGlobal StatisticsIntroductionNearest Neighbor StatisticQuadrat MethodsSpatial Dependence: Moran’s IGeary’s CA Comparison of Moran’s I and Geary’s COden’s Ipop StatisticTango’s Statistic and a Spatial Chi-Square StatisticGetis and Ord’s Global StatisticCase?Control Data: The Cuzick?Edwards TestA Global Quadrat Test of Clustering for Case?Control DataA Modified Cuzick?Edwards TestLocal StatisticsIntroductionLocal Moran StatisticScore StatisticTango’s CF StatisticGetis’ Gi StatisticStone’s TestModeling around Point Sources with Case?Control DataCumulative and Maximum Chi-Square Tests as Focused TestsThe Local Quadrat Test and an Introduction to Multiple Testing via the M-TestTests for the Detection of Clustering, Including Scan StatisticsIntroductionOpenshaw et al.’s Geographical Analysis Machine (GAM)Besag and Newell’s Test for the Detection of ClustersFotheringham and Zhan’s MethodCluster Evaluation Permutation ProcedureExploratory Spatial Analysis Approach of Rushton and LolonisKulldorff’s Spatial Scan Statistic with Variable Window SizeBonferroni and Sidak AdjustmentsImprovements on the Bonferroni AdjustmentRogerson’s Statistical Method for the Detection of Geographic ClusteringRetrospective Detection of Changing Spatial PatternsIntroductionThe Knox Statistic for Space?Time InteractionTest for a Change in Mean for a Series of Normally Distributed ObservationsRetrospective Detection of Change in Multinomial ProbabilitiesIntroduction to Statistical Process Control and Nonspatial Cumulative Sum Methods of SurveillanceIntroductionShewhart ChartsCumulative Sum (Cusum) MethodsMonitoring Small CountsCumulative Sums for Poisson VariablesCusum Methods for Exponential DataOther Useful Modifications for Cusum ChartsMore on the Choice of Cusum ParametersOther Methods for Temporal SurveillanceSpatial Surveillance and the Monitoring of Global StatisticsBrief Overview of the Development of Methods for Spatial SurveillanceIntroduction to Monitoring Global Spatial StatisticsCumulative Sum Methods and Global Spatial Statistics That Are Observed PeriodicallyCUSUM Methods and Global Spatial Statistics That Are Updated PeriodicallySummary and DiscussionCusum Charts for Local Statistics and for the Simultaneous Monitoring of Many RegionsMonitoring around a Predefined LocationSpatial Surveillance: Separate Charts for Each RegionMonitoring Many Local Statistics SimultaneouslySummaryAppendixMore Approaches to the Statistical Surveillance of Geographic ClusteringIntroductionMonitoring Spatial MaximaMultivariate Cusum ApproachesSummary:Associated Tests for Cluster Detection and SurveillanceIntroductionAssociated Retrospective Statistical TestsAssociated Prospective Statistical Tests: Regional Surveillance for Quick Detection of ChangeReferencesAuthor IndexSubject Index