Evaluating geographic imputation approaches for zip code level data: an application to a study of pediatric diabetes
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* Corresponding author: Angela D Liese liese@sc.edu
1 Department of Epidemiology and Biostatistics and Center for Research in Nutrition and Health Disparities, Arnold School of Public Health, University of South Carolina, 921 Assembly Street, Columbia, SC, USA
2 Medical University of South Carolina College of Medicine, 135 Cannon Street, Suite 303, Charleston, SC, USA
3 Department of Environmental Health Sciences, Arnold School of Public Health, University of South Carolina, 921 Assembly Street, Columbia, SC, USA
4 Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, 800 Sumter Street, Columbia, SC, USA
5 South Carolina Cancer Prevention and Control Program, University of South Carolina, 915 Greene Street, Columbia, SC, USA
6 Children's Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH, USA
7 University of Washington Child Health Institute, Seattle, WA, USA
8 University of Colorado School of Public Health, 13001 East 17th Avenue, Denver, CO, USA
International Journal of Health Geographics 2009, 8:54 doi:10.1186/1476-072X-8-54
Published: 8 October 2009Additional files
Additional file 1:
Group level geo-imputation accuracy. Table summarizing group level geo-imputation accuracy across all four study sites.
Format: DOC Size: 66KB Download file
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