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The Impact of Data Suppression on Local Mortality Rates: The Case of CDC WONDER.

CDC WONDER (Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research) is the nation's primary data repository for health statistics. Before WONDER data are released to the public, data cells with fewer than 10 case counts are suppressed. We showed that maps prod...

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Publicado en:American Journal of Public Health Vol. 104; no. 8; pp. 1386 - 1389
Autores principales: Tiwari, Chetan, Beyer, Kirsten, Rushton, Gerard
Formato: Journal Article
Publicado: American Public Health Association Aug2014
Materias:
United States
Centers for Disease Control & Prevention (U.S.)
Heart disease related mortality
Mortality
Census
Health policy
Algorithms
Statistical correlation
Databases
Epidemiological research
Maps
Research evaluation
Statistics
Acceso en línea:Ver este registro en EBSCOhost
Sumario:CDC WONDER (Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research) is the nation's primary data repository for health statistics. Before WONDER data are released to the public, data cells with fewer than 10 case counts are suppressed. We showed that maps produced from suppressed data have predictable geographic biases that can be removed by applying population data in the system and an algorithm that uses regional rates to estimate missing data. By using CDC WONDER heart disease mortality data, we demonstrated that effects of suppression could be largely overcome.