| Literature DB >> 20234799 |
Abstract
Most disease clustering methods assume specific shapes and do not evaluate statistical power using the applicable geography, at-risk population, and covariates. Cluster Morphology Analysis (CMA) conducts power analyses of alternative techniques assuming clusters of different relative risks and shapes. Results are ranked by statistical power and false positives, under the rationale that surveillance should (1) find true clusters while (2) avoiding false clusters. CMA then synthesizes results of the most powerful methods. CMA was evaluated in simulation studies and applied to pancreatic cancer mortality in Michigan, and finds clusters of flexible shape while routinely evaluating statistical power.Entities:
Keywords: Clustering methods; medical geography; meta-analysis; statistical power
Mesh:
Year: 2009 PMID: 20234799 PMCID: PMC2838429 DOI: 10.1016/j.sste.2009.08.002
Source DB: PubMed Journal: Spat Spatiotemporal Epidemiol ISSN: 1877-5845