Autore
Liseo, Brunero

Titolo
A novel Bayesian approach to matching and size population problems
Periodico
Università degli Studi di Roma "La Sapienza" - Dipartimento di Studi Geoeconomici, Linguistici, Statistici e Storici per l'Analisi regionale. Working papers
Anno: 2009 - Fascicolo: 65 - Pagina iniziale: 1 - Pagina finale: 22

We propose and illustrate a novel hierarchical Bayesian approach for matching statistical records observed in different occasions. We show how this model can be profitably adopted both in record linkage problems and in capture-recapture setups,where the size of a finite population is the real object of interest. There are at least two important differences among the proposed model-based approach and the current practice in record linkage: the statistical model is built up on the actually observed categorical variables and no reduction (to 0-1 comparisons) of the available information takes place. Second, the model is flexible enough to be used both for record linkage tasks and population size estimation problems. Among the many pros of a Bayesian approach we need to mention that the hierarchical structure of the model allows a two-way propagation of the uncertainty between the parameter estimation step and the matching procedure: no plug-in estimates are used. We illustrate and motivate the method through a real data problem.




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