The application of K-function analysis to the geographical distribution of road traffic accident outcomes in Norfolk, England
Andrew P. Jones,
Ian H. Langford and
Graham Bentham
Social Science & Medicine, 1996, vol. 42, issue 6, 879-885
Abstract:
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.
Keywords: K-functions; spatial-statistics; GIS; road-traffic-accidents (search for similar items in EconPapers)
Date: 1996
References: Add references at CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0277-9536(95)00186-7
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:socmed:v:42:y:1996:i:6:p:879-885
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
http://www.elsevier. ... _01_ooc_1&version=01
Access Statistics for this article
Social Science & Medicine is currently edited by Ichiro (I.) Kawachi and S.V. (S.V.) Subramanian
More articles in Social Science & Medicine from Elsevier
Bibliographic data for series maintained by Catherine Liu ().