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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
ANSELIN, L. (1988): Spatial Econometrics: Methods and Models. Dordrecht, Kluwer Academic Publishers.
BARTLETT, M. (1966): Stochastic Processes. Cambridge University Press.
BESAG, J.E. (1974): Spatial interaction and the statistical analysis of lattice systems. Journal, Royal Statistical Society, B36, 192–236.
CARSTAIRS, V. (1981): Small area analysis and health service research. Community Medicine, 3(2): 131–139.
CLAYTON, D. and KALDOR, J. (1987): Empirical Bayes estimates of age standardised relative risks for use in disease mapping. Biometrics 43, pp. 671–681.
CLIFF, A., HAGGETT, P., et al (1975): Elements of Spatial Structure. Cambridge University Press.
CLIFF, A.D. and ORD, J.K. (1973): Spatial Autocorrelation. Pion, London.
CLIFF, A.D and ORD, J.K. (1981): Spatial Processes: Models and Applications. London, Pion.
CRESSIE, N. (1984): Towards resistant geostatistics. In G. Verly et al (eds) Geo-statistics for Natural Resources Characterization, 21–44. Dordrecht, Reidel.
CRESSIE, N. (1991): Statistics for Spatial Data, Wiley, New York.
CRESSIE, N. and READ, T.R.C. (1989): Spatial data analysis of regional counts. Biometrical Journal, 6, 699–719.
DIGGLE, P. (1983): Statistical Analysis of Spatial Point Patterns. Academic Press, London.
GEARY, R.C. (1954): The contiguity ratio and statistical mapping. The Incorporated Statistician, 5, 115–145.
GOODCHILD, M., HAINING, R.P. and WISE, S.M. (1992): Integrating Geographic Information Systems and Spatial Data Analysis: Problems and Possibilities. International Journal of Geographical Information Systems, 16, 407–24.
HAINING, R.P. (1993): Spatial data analysis in the social and environmental sciences. Cambridge University Press.
HAINING, R.P. (1994): Diagnostics for regression modelling in spatial econometrics. Journal of Regional Science, 34, 324–341.
HAINING, R.P., WISE, S.M. and BLAKE, M. (1994): Constructing regions for small area analysis: health service delivery and colorectal cancer (Unpublished ms).
HASLETT, J., BRADLEY, R., CRAIG, P.S. et ai (1991): Dynamic graphics for exploring spatial data with application to locating global and local anomalies American Statistician, 45, 234–242.
KENDALL, M.G. (1939): The geographical distribution of crop productivity in: England. Journal, Royal Statistical Society, 102, 21–48.
KRISHNA IYER, P.V.A. (1949): The first and second moments of some probability distributions on a lattice and their applications. Biometrika, 36, 135–41
MARSHALL, R.J. (1991): A review of methods for the statistical anaiaysis of spatial patterns of disease. Journal, Royal Statistical Society, A, 154, 421–441.
MARTIN, R.J. (1992): Leverage, influence and residuals in regression models when observations are correlated. Communications in Statistics: Theory and Methods, 21, 1183–1212.
MORAN, P.A.P. (1948): The interpretation of statistical maps. Journal, Royal Statistical Society, B, 10, 243–51.
OLIVER, M.A. and WEBSTER, R. (1989): A geostatistical basis for spatial weighting in multivariate classification. Mathematical Geology, 21, 15–35.
ORD, J.K. (1975): Estimation methods for models of spatial interaction. Journal, American Statistical Association, 70, 120–6.
POCOCK, S.J., COOK, D.G. and BERESFORD, S.A.A. (1981): Regressions of area mortality rates on explanatory variables: what weighting is appropriate? Applied Statistician 30, 286–96.
RIPLEY, B. (1977): Modelling Spatial Patterns (with discussion). Journal, Royal Statistical Society,B, 39, 172–212.
RIPLEY, B. (1981): Spatial Statistics. New York, Wiley.
SEMPLE, R. and GREEN, M. (1984): Classification in Human Geography. In G. Gaile and C. Willmott (eds): Spatial Statistics and Models. Reidel, Dordrecht.
STOYAN, D., KENDALL, W.S. and MECKE, J. (1989): Stochastic Geometry and its Applications. New York, Wiley.
UPTON, G.J. and FINGLETON, B. (1985): Spatial Data Analysis by Example Volume 1: Point Pattern and Quantitative Data. New York, Wiley.
WEISBERG, S. (1985): Applied Linear Regression. New York, Wiley.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1996 Springer-Verlag Berlin · Heidelberg
About this paper
Cite this paper
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
Download citation
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
eBook Packages: Springer Book Archive