PMC:1247195 / 39953-41229 JSONTXT

{"target":"https://pubannotation.org/docs/sourcedb/PMC/sourceid/1247195","sourcedb":"PMC","sourceid":"1247195","source_url":"https://www.ncbi.nlm.nih.gov/pmc/1247195","text":"We have shown that besides reporting and mapping the mean posterior relative risk, the whole posterior distribution can be usefully exploited to try to detect true raised-risk areas. For the BYM model, decision rules based on computing the probability that the relative risk is above 1 with a cutoff between 70 and 80% gives a specific rule. With this type of rule an average expected count of 20 in each of the raised-risk areas leads to a 50% chance of detecting a true relative risk of 1.5, but at least a 75% chance if the true relative risk is 2. For the same scenarios, the posterior mean relative risks are 1.05 and 1.23, respectively, showing that the posterior probabilities rather than the mean posterior relative risks are crucial for interpreting results from the BYM model. On the other hand, 3-fold increases in the relative risk are detected almost certainly with average expected counts of only 5 per area, although the mean of the posterior distribution is typically smoothed to about half the true excess. Note that the performance of the BYM model does improve when the risk is raised in a small group of contiguous areas with similar expected counts rather than in a single area because of the way spatial correlation is taken into account in these models.","tracks":[]}