Journal
STATISTICS IN MEDICINE
Volume 33, Issue 11, Pages 1928-1945Publisher
WILEY-BLACKWELL
DOI: 10.1002/sim.6078
Keywords
confidentiality; disclosure; geography; imputation; synthetic
Categories
Funding
- US National Institute of Health [1R21AG032458]
- US National Science Foundation [SES-11-31897]
- Direct For Social, Behav & Economic Scie
- Divn Of Social and Economic Sciences [1131897] Funding Source: National Science Foundation
Ask authors/readers for more resources
Data that include fine geographic information, such as census tract or street block identifiers, can be difficult to release as public use files. Fine geography provides information that ill-intentioned data users can use to identify individuals. We propose to release data with simulated geographies, so as to enable spatial analyses while reducing disclosure risks. We fit disease mapping models that predict areal-level counts from attributes in the file and sample new locations based on the estimated models. We illustrate this approach using data on causes of death in North Carolina, including evaluations of the disclosure risks and analytic validity that can result from releasing synthetic geographies. Copyright (c) 2014 John Wiley & Sons, Ltd.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available