| Autor: |
Kelsall JE; Mathematics, Lancaster University, UK., Diggle PJ |
| Jazyk: |
angličtina |
| Zdroj: |
Statistics in medicine [Stat Med] 1995 Nov 15-30; Vol. 14 (21-22), pp. 2335-42. |
| DOI: |
10.1002/sim.4780142106 |
| Abstrakt: |
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. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
|
Plný text