Probabilistic population estimation of the size and overlap of data sets based on date of birth

Probabilistic population estimation is a statistical procedure for deriving unduplicated counts of the number of people represented in data sets that do not include unique person identifiers and the number of people shared by data sets that do not share personal identifiers. Because the procedure re...

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Bibliographic Details
Published in:Statistics in medicine 2001-05, Vol.20 (9-10), p.1421-1430
Main Authors: Banks, Steven M., Pandiani, John A.
Format: Article
Language:English
Subjects:
Age Factors
Biological and medical sciences
Computer Simulation
Computerized, statistical medical data processing and models in biomedicine
Confidentiality
Data Interpretation, Statistical
Databases, Factual
Female
Humans
Male
Medical sciences
Medical statistics
Models, Biological
Models, Statistical
Population Dynamics
Public Policy
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Summary:Probabilistic population estimation is a statistical procedure for deriving unduplicated counts of the number of people represented in data sets that do not include unique person identifiers and the number of people shared by data sets that do not share personal identifiers. Because the procedure relies on anonymous data sets, the personal privacy of individuals and the confidentiality of medical records is protected. This paper describes the mathematics of probabilistic population estimation, and applies the procedure to an important contemporary public policy issue. Copyright © 2001 John Wiley & Sons, Ltd.
ISSN:0277-6715
1097-0258
DOI:10.1002/sim.679