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.Abstract
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.
| Item Type: | Article |
|---|---|
| Journal or Publication Title: | Statistics in Medicine |
| Subjects: | R Medicine > R Medicine (General) |
| Departments: | Faculty of Health and Medicine > Medicine VC's Office |
| ID Code: | 19574 |
| Deposited By: | ep_ss_importer |
| Deposited On: | 11 Nov 2008 08:54 |
| Refereed?: | Yes |
| Published?: | Published |
| Last Modified: | 26 Jul 2012 15:32 |
| Identification Number: | |
| URI: | http://eprints.lancs.ac.uk/id/eprint/19574 |
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