Detection of spatial clusters and outliers in cancer rates using geostatistical filters and spatial neutral models

  • P. Goovaerts
Conference paper


Spatial Cluster Cancer Rate Neutral Model Sequential Gaussian Simulation Spatial Outlier 
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  1. Anselin L (1995) Local indicators of spatial association — LISA. Geographical Analysis 27: 93–115Google Scholar
  2. Anselin L, Syabri I, Kho Y (2004) GeoDa: An Introduction to Spatial Data Analysis. Spatial Analysis Laboratory (SAL). Department of Agricultural and Consumer Economics, University of Illinois, Champaigne-Urbana, ILGoogle Scholar
  3. Assunçao RM, Reis EA (1999) A new proposal to adjust Moran’s I for population density. Statistics in Medicine 18:2147–2162Google Scholar
  4. Cressie N (1993) Statistics for Spatial Data. Wiley, New YorkGoogle Scholar
  5. Goovaerts P (1997) Geostatistics for Natural Resources Evaluation. Oxford University Press New YorkGoogle Scholar
  6. Goovaerts P, Jacquez GM (2004) Accounting for regional background and population size in the detection of spatial clusters and outliers using geostatistical filtering and spatial neutral models: the case of lung cancer in Long Island, New York. International Journal of Health Geographics 3:14CrossRefGoogle Scholar
  7. Goovaerts P (2005) Simulation-based assessment of a geostatistical approach for estimation and mapping of the risk of cancer. In: Leuangthong O and Deutsch CV (eds) Geostatistics Banff 2004. Kluwer Academic Publishers, Dordrecht, The Netherlands, in reviewGoogle Scholar
  8. Goovaerts P, Jacquez GM, Greiling DA (2005) Exploring scale-dependent correlations between cancer mortality rates using factorial kriging and population-weighted semivariograms. Geographical Analysis, 37, in pressGoogle Scholar
  9. Gotway CA, Young LJ (2002) Combining incompatible spatial data. Journal of the American Statistical Association 97:632–648CrossRefGoogle Scholar
  10. Jacquez GM, Greiling DA (2003a) Local clustering in breast, lung and colorectal cancer in Long Island, New York. International Journal of Health Geographics 2:3Google Scholar
  11. Jacquez GM, Greiling DA (2003b) Geographic boundaries in breast, lung and colorectal cancer in relation to exposure to air toxics in Long Island, New York. International Journal of Health Geographics 2:4Google Scholar
  12. Oliver MA, Webster R, Lajaunie C, Muir KR, Parkes SE, Cameron AH, Stevens MCG, Mann JR (1998) Binomial cokriging for estimating and mapping the risk of childhood cancer. IMA Journal of Mathematics Applied in Medicine and Biology 15:279–297Google Scholar
  13. Ord JK, Getis A (2001) Testing for local spatial autocorrelation in the presence of global autocorrelation. Journal of Regional Science 41: 411–432CrossRefGoogle Scholar
  14. Rivoirard J. et al. (2000) Geostatistics for Estimating Fish Abundance. Blackwell Science, OxfordGoogle Scholar
  15. Waller LA, Gotway CA (2004) Applied Spatial Statistics for Public Health Data. John Wiley and Sons, New JerseyGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • P. Goovaerts
    • 1
  1. 1.BioMedware, Inc.Ann ArborUSA

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