Social Indicators Research

, Volume 82, Issue 2, pp 287–309 | Cite as

Using Exploratory Spatial Data Analysis to Leverage Social Indicator Databases: The Discovery of Interesting Patterns



With the proliferation of social indicator databases, the need for powerful techniques to study patterns of change has grown. In this paper, the utility of spatial data analytical methods such as exploratory spatial data analysis (ESDA) is suggested as a means to leverage the information contained in social indicator databases. The principles underlying ESDA are illustrated using a study of clusters and outliers based on data for a child risk scale computed for countries in the state of Virginia. Evidence of spatial clusters of high child risks is obtained along the Southern region of Virginia. The utility of spatial methods for state agencies in monitoring social indicators at various localities is discussed. A six-step framework that integrates spatial analysis of key indicators within a monitoring framework is presented; we argue that such a framework could be useful in enhancing communication between State and local planners.


spatial analysis global association local association Community Health Indicators state-level planning 


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  1. Annie E. Casey Foundation (2003) Kids Count. Annie E Casey, Baltimore, MDGoogle Scholar
  2. Annie E. Casey Foundation: 2005, Kids Count Data Book (Annie E Casey, Baltimore, MD)Google Scholar
  3. Anselin L. (1988) Spatial Econometrics: Methods and Models. Kluwer Academic, DodrechtGoogle Scholar
  4. Anselin L (1994) Exploratory spatial data analysis and geographic information systems. In: M. Painho (eds) New Tools for Spatial Analysis (Eurostat, Luxembourg), pp. 45–54Google Scholar
  5. Anselin L. (1995) Local indicators of spatial association-LISA, Geographical Analysis 27:93–115CrossRefGoogle Scholar
  6. Anselin L. (1999a) The future of spatial analysis in the social sciences. Geographical Information Sciences 5:67–76Google Scholar
  7. Anselin L. (1999b) Interactive techniques and exploratory spatial data analysis. In: P. Longley, M. Goodchild, D. Maguire, D. Rhind (eds) Geographical Information Systems: Principles, Techniques, Management and Applications ( Wiley, New York), pp. 251–264Google Scholar
  8. Anselin, L. and A. Bera: 1998, ‚Spatial dependence in linear regression models with an introduction to spatial econometrics’, in A. Ullah and D. Giles (eds.), Handbook of Applied Economic Statistics (Marcel Dekker, New York)Google Scholar
  9. Anselin, L., Y.-W. Kim and I. Syabri: 2004, ‚Web-based analytical tools for the exploration of spatial data’, Journal of Geographical Systems 6, pp. 197–218Google Scholar
  10. Anselin, L., I. Syabri and Y. Kho: 2006, ‘GeoDa: An Introduction to Spatial Data Analysis’, Geographical Analysis 38, pp. 5–22Google Scholar
  11. Anselin, L., I. Syabri and O. Smirnov: 2002, ‚Visualizing multivariate spatial correlation with dynamically linked windows’, in L. Anselin and S. Rey (eds.), New Tools for Spatial Data Analysis: Proceedings of a Workshop (Center for Spatially Integrated Social Science, Santa Barbara)Google Scholar
  12. Bramstedt, N. and W. O’Hare: 2002, ‘Examining Inter-Relationships Among State-level Measures of Child Well-Being’, (Annie E Casey, Baltimore, MD). final 1.1 18.pdfGoogle Scholar
  13. Buja A., Cook D., Swayne D. (1996) Interactive high dimensional data visualization. Journal of Computational and Graphical Statistics 5:78–99CrossRefGoogle Scholar
  14. Clayton D.G., Kaldor J. (1987) Empirical Bayes estimates of age-standardized relative risks for use in disease mapping. Biometrics 43: 671–691CrossRefGoogle Scholar
  15. Cliff A.D., Ord J.K. (1981) Spatial Processes, Models and Applications. Pion, LondonGoogle Scholar
  16. Cressie N. (1993) Statistics for Spatial Data. Wiley, New YorkGoogle Scholar
  17. Dorling, D.: 1996, Area Cartograms: Their Use and Creation. CATMOG 59 (Institute of British Geographers)Google Scholar
  18. Goodchild M., Anselin L., Appelbaum R., Harthorn B. (2000) Towards spatially integrated social science. International Regional Science Review 23:139–159Google Scholar
  19. Hawkins J., Catalano R. (1992) Communities That Care: Action for Drug Abuse Prevention. Jossey-Bass, San FranciscoGoogle Scholar
  20. Hugo G. (1994) GIS & socio-economics. GIS User 6:46–47Google Scholar
  21. Kids Count: 1999, 1999 KIDS COUNT Online. (Annie E Casey, Baltimore, MD). 1999/overview.htmGoogle Scholar
  22. Kirby, R. and S. Foldy: 1998, ‚The role of geographic information systems in population health’, in R.Williams, M. Howie, C. Lee and W. Henriques (eds.), Geographic Information Systems in Public Health: Proceedings of the Third National Conference, (Centers for Disease Control, Atlanta, pp. 579–587Google Scholar
  23. Land K., Lamb V., Mustillo S. (2001) Child and youth well-being in the United States, 1975–1998: Some findings from a new index. Social Indicators Research 56:241–318CrossRefGoogle Scholar
  24. Marshall R. (1991) Mapping disease and mortality rates using empirical Bayes estimators. Applied Statistics 40:283–294CrossRefGoogle Scholar
  25. Messner S., Anselin L. (2004) Spatial analyses of homicide with areal data. In: M. Goodchild, D. Janelle (eds) Spatially Integrated Social Science (Oxford University Press), New York, pp. 127–144Google Scholar
  26. Page, P.: 1993. ‚GIS & social sciences’, in Proceedings of the Thirteenth Annual ESRI Conference, Vol. I (ESRI, Los Angeles), pp. 385–396Google Scholar
  27. Plane D., Rogerson P. (1994) The Geographical Analysis of Population with Applications to Planning & Business. John Wiley & Sons, New YorkGoogle Scholar
  28. Sampson, R.: 1993, ‚Linking time & place: Dynamic contextualism and the future of criminological inquiry’, Journal of Research in Crime & Delinquency 30, pp. 426–444Google Scholar
  29. Society for Prevention Research (2003) Community Level Monitoring. Scholar
  30. Tukey J. (1977) Exploratory Data Analysis. Addison-Wesley, ReadingGoogle Scholar
  31. Upton G., Fingleton B. (1985) Spatial Data Analysis by Example. Wiley, New YorkGoogle Scholar
  32. Voices for Virginia’s Children (2005) Virginia Kids Count Data Book. Voices for Virginia’s Children, Richmond, VAGoogle Scholar

Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  • Luc Anselin
    • 2
  • Sanjeev Sridharan
    • 1
  • Susan Gholston
    • 3
  1. 1.The Evaluation Programme, Research Unit in Health, Behaviour and Change Community Health Sciences, RUHBCThe University of Edinburgh, Medical SchoolEdinburghUK
  2. 2.University of Illinois at Urbana–Champaign and NCOVRUrbanaUSA
  3. 3.Virginia Department of Juvenile JusticeRichmondUSA

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