Lancaster EPrints

Non-parametric estimation of spatial variation in relative risk.

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

Actions (login required)

View Item