Statistics and Public Policy · 2014 · 38 citations · 16 references
Public HealthBiostatisticsOncologyCancer EpidemiologyEpidemiologic MethodsEpidemiologyBayesian Spatial AnalysisBayesian StatisticsCancer ClusteringGeographic Variation In CancerSpatial Cluster AnalysisSpatial Distribution Of DiseaseExcess Risk ModelRelative Risk EstimationSpatial Cancer ClusteringSpatial Cluster InferenceSpatial Clustering AnalysisSpatial Clustering Of DiseaseSpatial Epidemiology Of CancerSpatial Relative Risk Analysis
In this article, we focus on geocoded data for pediatric brain cancer in Florida. Specifically, we examine zip code level pediatric brain cancer counts from the Florida Association of Pediatric Tumor Programs (FAPTP) childhood cancer registry from 2000–2010 and assess the degree of spatial clustering in these data. We assume Bayesian models for relative risk and examine a variety of posterior measures that indicate excess risk (exceedence probability of relative risk or positive residual). We assume a standard Poisson convolution model and examine a zero-inflated (ZI) model with a factored intercept. We conclude that there is evidence of excess risk in a number of relatively dispersed zip codes across the state but there appears to be some concentration of high excess risk in Polk, Lake, and Sumter counties (west of Orlando and north east of Tampa). These excesses are confirmed across the models.
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