A hierarchical Bayesian approach to record linkage and population size problems

Statistics – Applications

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Published in at http://dx.doi.org/10.1214/10-AOAS447 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Ins

Scientific paper

10.1214/10-AOAS447

We propose and illustrate a hierarchical Bayesian approach for matching statistical records observed on 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 between the proposed model-based approach and the current practice in record linkage. First, 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 hierarchical structure of the model allows a two-way propagation of the uncertainty between the parameter estimation step and the matching procedure so that no plug-in estimates are used and the correct uncertainty is accounted for both in estimating the population size and in performing the record linkage. We illustrate and motivate our proposal through a real data example and simulations.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

A hierarchical Bayesian approach to record linkage and population size problems does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A hierarchical Bayesian approach to record linkage and population size problems, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A hierarchical Bayesian approach to record linkage and population size problems will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-430997

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.