Journal
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS
Volume 61, Issue -, Pages 99-115Publisher
WILEY
DOI: 10.1111/j.1467-9876.2011.01004.x
Keywords
Integrated nested Laplace approximation; Bayesian inference; Changing boundaries; Disease mapping
Categories
Funding
- Natural Sciences and Engineering Research Council of Canada
- Cancer Care Ontario's Population Studies Network
Ask authors/readers for more resources
. Clinical data on the location of residence at the time of diagnosis of new lupus cases in Toronto, Canada, for the 40 years to 2007 are modelled with the aim of finding areas of abnormally high risk. Inference is complicated by numerous irregular changes in the census regions on which population is reported. A model is introduced consisting of a continuous random spatial surface and fixed effects for time and ages of individuals. The process is modelled on a fine grid and Bayesian inference performed by using integrated nested Laplace approximations. Predicted risk surfaces and posterior probabilities of exceedance are produced for lupus and, for comparison, psoriatic arthritis data from the same clinic. Simulations studies are also carried out to understand better the performance of the model proposed as well as to compare with existing methods.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available