Summary
The paper classifies the main forms of spatial analysis and briefly reviews advances in spatial analysis over the last twenty years. The paper then considers three problem areas using health data for illustration: (i) how to construct a spatial framework for analysis; (ii) how to construct reliable area rates that recognize the spatial distribution of areas and their variable populations; (iii) how to test for relationships between variables when rates vary in reliability and there may be spatial autocorrelation in the unexplained variation. The paper briefly considers the potentially important role of geographic information systems in the field of spatial data analysis.
Keywords
- Geographic Information System
- Spatial Autocorrelation
- Spatial Analysis
- Spatial Data
- Royal Statistical Society
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© 1996 Springer-Verlag Berlin · Heidelberg
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Haining, R. (1996). Classifying Space and Analysing the Consequences: Spatial Analysis of Health Data. In: Gaul, W., Pfeifer, D. (eds) From Data to Knowledge. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-79999-0_4
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DOI: https://doi.org/10.1007/978-3-642-79999-0_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-60354-2
Online ISBN: 978-3-642-79999-0
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