Kelsall, Julia E. and Diggle, Peter J. (1995) Non-parametric estimation of spatial variation in relative risk. Statistics in Medicine, 14 (21-22). pp. 2335-2342.Full text not available from this repository.
We consider the problem of estimating the spatial variation in relative risks of two diseases, say, over a geographical region. Using an underlying Poisson point process model, we approach the problem as one of density ratio estimation implemented with a non-parametric kernel smoothing method. In order to assess the significance of any local peaks or troughs in the estimated risk surface, we introduce pointwise tolerance contours which can enhance a greyscale image plot of the estimate. We also propose a Monte Carlo test of the null hypothesis of constant risk over the whole region, to avoid possible over-interpretation of the estimated risk surface. We illustrate the capabilities of the methodology with two epidemiological examples.
|Journal or Publication Title:||Statistics in Medicine|
|Subjects:||R Medicine > R Medicine (General)|
|Departments:||Faculty of Health and Medicine > Medicine|
|Deposited On:||11 Nov 2008 08:54|
|Last Modified:||26 Jul 2012 15:32|
Actions (login required)