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Searching For Leukaemia Clusters Using A Geographical Analysis Machine

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  • Stan Openshaw
  • Martin Charlton
  • Alan Craft

Abstract

ABSTRACT The paper describes a new approach to the graphical analysis of cancer data. A Geographical Analysis Machine is built which simultaneously solves the problems of post hot: hypothesis testing, handling data errors, and the task of generating and evaluating hypotheses in an exploratory environment. The methodology is demonstrated by reanalyzing cancer data for Northern England in such a way that for the first time the complex universe of all geographical hypotheses is enumerated, evaluated, and all the significant cancer clusters displayed.

Suggested Citation

  • Stan Openshaw & Martin Charlton & Alan Craft, 1988. "Searching For Leukaemia Clusters Using A Geographical Analysis Machine," Papers in Regional Science, Wiley Blackwell, vol. 64(1), pages 95-106, January.
    • Handle: RePEc:bla:presci:v:64:y:1988:i:1:p:95-106
    DOI: 10.1111/j.1435-5597.1988.tb01117.x
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    Cited by:

    1. Michael Poulsen & Ron Johnston & James Forrest, 2010. "The Intensity of Ethnic Residential Clustering: Exploring Scale Effects Using Local Indicators of Spatial Association," Environment and Planning A, , vol. 42(4), pages 874-894, April.

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