IJHG

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Open Access Research

Evaluating geographic imputation approaches for zip code level data: an application to a study of pediatric diabetes

James D Hibbert1, Angela D Liese1*, Andrew Lawson2, Dwayne E Porter3, Robin C Puett3,4,5, Debra Standiford6, Lenna Liu7 and Dana Dabelea8

Author Affiliations

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

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International Journal of Health Geographics 2009, 8:54 doi:10.1186/1476-072X-8-54

Published: 8 October 2009

Additional 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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Open Data