Integrated methodology for multiple systems estimation and record linkage using a missing data formulation |
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Authors: | Stephen E. Fienberg Daniel Manrique-Vallier |
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Affiliation: | (1) Department of Statistics, Carnegie Mellon University, Pittsburgh, PA, USA;(2) Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA, USA |
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Abstract: | There are now three essentially separate literatures on the topics of multiple systems estimation, record linkage, and missing data. But in practice the three are intimately intertwined. For example, record linkage involving multiple data sources for human populations is often carried out with the expressed goal of developing a merged database for multiple system estimation (MSE). Similarly, one way to view both the record linkage and MSE problems is as ones involving the estimation of missing data. This presentation highlights the technical nature of these interrelationships and provides a preliminary effort at their integration. |
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Keywords: | Capture– recapture Heterogeneity Data fusion EM algorithm Fellegi– Sunter linkage Missing data |
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