The application of K-function analysis to the geographical distribution of road traffic accident outcomes in Norfolk, England

• Published in: Social science & medicine (1982) Vol. 42; no. 6; pp. 879 - 885
• Main Authors: Jones, Andrew P., Langford, Ian H., Bentham, Graham
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.03.1996; Elsevier; Pergamon Press Inc
• Series: Social Science & Medicine
• Subjects: Accidents, Traffic - mortality; Adolescent; Adult; Aged; Cluster Analysis; Data Interpretation, Statistical; England; Epidemiologic Methods; Fatalities; Female; Geographic distribution; Geographic information systems; Geographical information systems; GIS; Humans; K-function analysis; K-functions; K-functions spatial-statistics GIS road-traffic-accidents; Logistic Models; Male; Middle Aged; Models, Statistical; Morbidity; Mortality; Norfolk; Outcomes; Regression Analysis; Road accidents; road-traffic-accidents; Spatial distribution; spatial-statistics; Traffic accidents & safety; United Kingdom; United Kingdom > UK; England; Norfolk England; GIS; K-functions; spatial-statistics; road-traffic-accidents
• ISSN: 0277-9536; 1873-5347
• DOI: 10.1016/0277-9536(95)00186-7

One method applicable to the examination of spatial point patterns of disease, the calculation of K-functions, is presented. The technique is used to determine the degree of clustering exhibited by the residuals from a spatially referenced logit model constructed to ascertain the factors influencing the likelihood of death in a road traffic accident. This was done to test if there was some systematic geographical factor influencing outcome not adequately controlled for in the model. K-functions are extremely versatile, overcoming many of the problems of incorporating the notion of scale associated with traditional methods of spatial autocorrelation. Recently software has become available which allows their calculation in an easy to use Geographical Information System style environment. This study illustrates the relevance of the method, not only to the analysis of data on mortality and morbidity, but also to the examination of the residuals from any spatial regression.