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. ISSN 1097-0258

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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:
Journal Article
Journal or Publication Title:
Statistics in Medicine
Uncontrolled Keywords:
/dk/atira/pure/researchoutput/libraryofcongress/r1
Subjects:
ID Code:
19574
Deposited By:
Deposited On:
11 Nov 2008 08:54
Refereed?:
Yes
Published?:
Published
Last Modified:
12 Mar 2020 02:08