• Statistics in medicine · Nov 1995

    Non-parametric estimation of spatial variation in relative risk.

    • J E Kelsall and P J Diggle.
    • Mathematics, Lancaster University, UK.
    • Stat Med. 1995 Nov 15; 14 (21-22): 2335-42.

    AbstractWe 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.

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