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

Abstract

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.