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 legit 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.
| Original language | English |
|---|---|
| Pages (from-to) | 879-885 |
| Number of pages | 7 |
| Journal | Social Science and Medicine |
| Volume | 42 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 1 Mar 1996 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- K-functions
- spatial-statistics
- GIS
- road-traffic-accidents
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