Wombling Analysis of Childhood Tumor Rates in Florida

References

• Amin, R., Bohnert, A., Holmes, L., Rajasekaran, A., and Assanasen, C. (2010), “Epidemiologic Mapping of Florida Childhood Cancer Clusters,” Pediatric Blood and Cancer, 54, 511–518.
   PubMed Web of Science ®Google Scholar
• Assuncao, R., Costa, M., Tavares, A., and Ferreira, F. (2006), “Fast Detection of Arbitrarily Shaped Disease Clusters,” Statistics in Medicine, 25, 723–742.
   PubMed Web of Science ®Google Scholar
• Diggle, P. J. (2003), Statistical Analysis of Spatial Point Patterns, London,UK: Arnold.
   Google Scholar
• Duczmal, L., and Assuncao, R. (2004), “A Simulated Annealing Strategy for the Detection of Arbitrarily Shaped Spatial Clusters,” Computational Statistics and Data Analysis, 45, 269–286.
   Web of Science ®Google Scholar
• Hodges, J. S., and Reich, B. J. (2010), “Adding Spatially-Correlated Errors Can Mess up the Fixed Effect You Love,” The American Statistician, 64, 325–334.
   Web of Science ®Google Scholar
• Hughes, J., and Haran, M. (2013), “Dimension Reduction and Alleviation of Confounding for Spatial Generalized Linear Mixed Models,” Journal of the Royal Statistical Society, 75, 139–159.
   Google Scholar
• Kulldorff, M. (1997), “A Spatial Scan Statistic,” Communications in Statistics—Theory and Methods, 26, 1481–1496.
   Web of Science ®Google Scholar
• Kulldorff, M., Huang, L., Pickle, L., and Duczmal, L. (2006), “An Elliptic Spatial Scan Statistic,” Statistics in Medicine, 25, 3929–3943.
   PubMed Web of Science ®Google Scholar
• Lawson, A. B. (2001), Statistical Methods in Spatial Epidemiology, New York: Wiley.
   Google Scholar
• ——— (2008), Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Boca Raton, FL: Chapman and Hall/CRC.
   Google Scholar
• Lee, D., and Mitchell, R. (2012), “Boundary Detection in Disease Mapping Studies,” Biostatistics, 13, 415–426.
   PubMed Web of Science ®Google Scholar
• Li, P., Banerjee, S., Hanson, T. E., and McBean, A. M. (2011a), “Nonparametric Hierarchical Modeling for Detecting Boundaries in Areally Referenced Spatial Datasets,” technical Report rr2010-014, Divison of Biostatistics, School of Public Health, University of Minnesota, Twin Cities.
   Google Scholar
• Li, P., Banerjee, S., and McBean, A. M. (2011b), “Mining Boundary Effects in Areally Referenced Spatial Data Using the Bayesian Information Criterion,” Geoinformatica, 15, 435–454.
   Web of Science ®Google Scholar
• Liang, S., Banerjee, S., and Carlin, B. P. (2009), “Bayesian Wombling for Spatial Point Processes,” Biometrics, 65, 1243–1253.
   PubMed Web of Science ®Google Scholar
• Lu, H., and Carlin, B. P. (2005), “Bayesian Areal Wombling for Geographical Boundary Analysis,” Geographical Analysis, 37, 265–285.
   Web of Science ®Google Scholar
• Lu, H., Reilly, C. S., Banerjee, S., and Carlin, B. P. (2007), “Bayesian Areal Wombling via Adjacency Modeling,” Environmental and Ecological Statistics, 14, 433–452.
   Web of Science ®Google Scholar
• Ma, H., and Carlin, B. P. (2007), “Bayesian Multivariate Areal Wombling for Multiple Disease Boundary Analysis,” Bayesian Analysis, 2, 281–302.
   Web of Science ®Google Scholar
• Møller, J., and Waagepeterson, R. P. (2004), Statistical Inference and Simulation for Spatial Point Processes, Boca Raton, FL: Chapman and Hall/CRC Press.
   Google Scholar
• Neill, D. B., Moore, A. W., and Cooper, G. F. (2006), “A Bayesian Spatial Scan Statistic,” in Advances in Neural Information and Processing Systems 18, eds. Y. Weiss, B. Scholkopf, and J. Platt, . Cambridge, MA: MIT Press, pp. 1003–1010.
   Google Scholar
• Wakefield, J., and Lyons, H. (2010), “Spatial Aggregation and the Ecological Fallacy,” in Handbook of Spatial Statistics, eds. A. E. Gelfand, P. J. Diggle, M. Fuentes, and P. Guttorp, Boca Raton, FL: Chapman & Hall/CRC, pp. 541–558.
   Google Scholar
• Waller, L. A., Carlin, B. P., Xia, H., and Gelfand, A. E. (1997), “Hierarchical Spatio-Temporal Mapping of Disease Rates,” Journal of the American Statistical Association, 92, 607–617.
   Web of Science ®Google Scholar
• Walther, G. (2010), “Optimal and Fast Detection of Spatial Clusters With Scan Statistics,” The Annals of Statistics, 38, 1010–1033.
   Web of Science ®Google Scholar
• Zhou, H., and Lawson, A. B. (2008), “Ewma Smoothing and Bayesian Spatial Modeling for Health Surveillance,” Statistics in Medicine, 27, 5907–5928.
   PubMed Web of Science ®Google Scholar