Methods for Investigating Localized Clustering of Disease

Paperback | February 1, 1997

EditorF. E. Alexander

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Methods of investigating generalized spatial clustering of disease in human populations have only recently become available. This volume presents the outcome of a unique practical test of these methods, in which authors of several newly developed approaches evaluate their own blind analyses ofover 50 artificial datasets, some random, some generated by clustering processes. Results were then compared with the known spatial structure. An historical view of leukemia clustering is also included. This book will be of particular interest to epidemiologists and public health specialists with responsibliity of analysing childhood leukemia and other rare diseases for which the phenomenon of clustering may offer important clues to aetiology. It will also be useful for statisticians with aninterest in analysis of spatial distributions of rare disease.

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Methods of investigating generalized spatial clustering of disease in human populations have only recently become available. This volume presents the outcome of a unique practical test of these methods, in which authors of several newly developed approaches evaluate their own blind analyses ofover 50 artificial datasets, some random, s...

F. E. Alexander is at University of Edinburgh. P. Boyle is at European Institute of Oncology.

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Format:PaperbackDimensions:264 pages, 9.45 × 6.89 × 0.68 inPublished:February 1, 1997Publisher:Oxford University Press

The following ISBNs are associated with this title:

ISBN - 10:9283221354

ISBN - 13:9789283221357

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Table of Contents

ForewordF.E. Alexander and P. Boyle: Introduction1. P. Boyle, A.M. Walker and F.E. Alexander: Historical aspects of leukaemia clusters2. F.E. Alexander, J. Williams, P. Maisonnneuve and P. Boyle: The simulated data-sets3. R.J. Black, L. Sharp and J.D. Urquhart: Analysing the spatial distribution of disease using a method of constructing geographical areas of approximately equal population size4. C.R. Muirhead and B.K. Butland: Testing for over-dispersion using an adapted form of the Potthoff-Whittinghill method5. J. Cuzick and R. Edwards: Clustering methods based on k nearest neighbour distributions6. S. Openshaw: Using a geographical analysis machine to detect the presence of spatial clustering and the location of clusters in synthetic data7. J.N. Newell and J.E. Besag: The detection of small-area database anomalies8. All participants: Detailed results for selected data-sets9. All participants: Overview of results10. F.E. Alexander and P. Boyle: Editorial comments11. Individual investigators: Responses by individual authors to editorial commentsAppendices:1. All investigators: The data-sets2. R.J. Black, L. Sharp and J.D. Urquhart: Extension of the ISD method3. J. Cuzick and R. Edwards: Cuzick-Edwards one-sample and inverse two-sampling statistics4. S. Openshaw: Tests of clustering based on pattern-recognition procedures5. P.J. Diggle and S. Morris: Second-order analysis of spatial clustering6. N.H. Anderson: A scan statistic for detecting spatial clusters7. R. Wakeford, K. Binks, M. Gerrard and A. Wood: The CAS method8. M.A. Oliver, K.R. Muir, S.E. Parkes and R. Webster: Geostatistics for determining the risk of rare diseaseReferences