Cluster morphology analysis.
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.
Department of Environmental Health Sciences, The University of Michigan, School of Public Health, Ann Arbor, 48109-2029, USA. jacquez@biomedware.com
Geoffrey M
GM
Jacquez
D016000:Cluster Analysis; D005260:Female; D062306:Geography, Medical; D006801:Humans; D008297:Male; D008824:Michigan / Q000453:epidemiology; D015233:Models, Statistical; D010190:Pancreatic Neoplasms / Q000453:epidemiology*; D012107:Research Design; D012306:Risk; D016019:Survival Analysis
Clustering methods; medical geography; meta-analysis; statistical power