Design-Based Estimation with Record-Linked Administrative Files and a Clerical Review Sample

Abel Dasylva

doi:10.1515/jos-2018-0003

Abstract

This article looks at the estimation of an association parameter between two variables in a finite population, when the variables are separately recorded in two population registers that are also imperfectly linked. The main problem is the occurrence of linkage errors that include bad links and missing links. A methodology is proposed when clerical-reviews may reliably determine the match status of a record-pair, for example using names, demographic and address information. It features clerical-reviews on a probability sample of pairs and regression estimators that are assisted by a statistical model of comparison outcomes in a pair. Like other regression estimators, this estimator is design-consistent regardless of the model validity. It is also more efficient when the model holds.

References

Belin, T.R. and D.B. Rubin. 1995. “A Method for Calibrating False-Match Rates in Record Linkage.” Journal of the American Statistical Association 90: 694-707. Doi: http://dx.doi.org/10.2307/2291082.10.1080/01621459.1995.10476563
Open DOI Search in Google Scholar Back to article
Chambers, R. 2009. “Regression Analysis of Probability-Linked Data.” Official Statistics Research Series, vol. 4.
Search in Google Scholar Back to article
Chipperfield, J.O., G.R. Bishop, and P. Campbell. 2011. “Maximum Likelihood Estimation for Contingency Tables and Logistic Regression with Incorrectly Linked Data.” Survey Methodology 37: 13-24.
Search in Google Scholar Back to article
Dempster, A., N. Laird, and D. Rubin. 1977. “Maximum Likelihood from Incomplete Data via the EM Algorithm.” Journal of the Royal Statistical Society Series B 39: 1-38. Available at: http://www.jstor.org/stable/2984875 (accessed November 2017).10.1111/j.2517-6161.1977.tb01600.x
Search in Google Scholar Back to article
Deville, J.-C. and C.-E. Sa¨rndal. 1992. “Calibration Estimators in Survey Sampling”. Journal of the American Statistical Association 37: 376-382.10.1080/01621459.1992.10475217
Search in Google Scholar Back to article
Fellegi, I.P. and A.B. Sunter. 1969. “A Theory of Record Linkage.” Journal of the American Statistical Association 64: 1183-1210.10.1080/01621459.1969.10501049
Open DOI Search in Google Scholar Back to article
Fienberg, S., P. Hersh, A. Rinaldo, and Y. Zhou. 2009. “Maximum Likelihood in Latent Class Models for Contingency Table Data.” In Algebraic and Geometric Methods in Statistics, edited by Paolo Giblisco, Eva Riccomagno, Maria Piera Rogantin, and Henry P. Wynn, 7-62. New York: Cambridge University Press.10.1017/CBO9780511642401.003
Search in Google Scholar Back to article
Gill, L. 2001. Methods for Automatic Record Matching and Linkage and their Use in National Statistics. London: Office of National Statistics.
Search in Google Scholar Back to article
Guiver, T. 2011. Sampling-Based Clerical Review Methods in Probabilistic Linking. Canberra: Australia Bureau of Statistics.
Search in Google Scholar Back to article
Heasman, D. 2014. “Sampling a Matching Project to Establish the Linking Quality.” Survey Methodology Bulletin 72: 1-16.
Search in Google Scholar Back to article
Howe, G.R. 1981. “A Generalized Iterative Record Linkage Computer System for Use in Medical Follow-Up Studies.” Computers and Biomedical Research 14: 327-340.10.1016/0010-4809(81)90004-5
Open DOI Search in Google Scholar Back to article
Jaro, M.A. 1989. “Advances in Record Linkage Methodology to Matching the 1985 Census of Tampa, Florida.” Journal of the American Statistical Association 84: 414-420.10.1080/01621459.1989.10478785
Search in Google Scholar Back to article
Jiang, J. 2007. Linear and Generalized Linear Mixed Models and Their Applications. New York: Springer.
Search in Google Scholar Back to article
Kim, B.S. 1984. Studies of Multinomial Mixture Models. PhD thesis, Chapel Hill: University of North Carolina.
Search in Google Scholar Back to article
Lahiri, P. and D. Larsen. 2005. “Regression Analysis with Linked Data.” Journal of the American Statistical Association 100: 222-227. Available at: http://www.jstor.org/stable/27590532 (accessed November 14, 2017).10.1198/016214504000001277
Search in Google Scholar Back to article
Larsen, M. and D. Rubin. 2001. “Iterated Automated Record Linkage Using Mixture Models.” Journal of the American Statistical Association 96: 32-41.10.1198/016214501750332956
Open DOI Search in Google Scholar Back to article
Lavalleé, P. 2002. Le Sondage indirect ou la me´thode du partage des poids. Bruxelles: E ´ ditions de l’Universite´ de Bruxelles.
Search in Google Scholar Back to article
Newcombe, H.B., M.E. Smith, and G.R. Howe. 1983. “Reliability of Computerized Versus Manual Death Searches in a Study of the Health of Eldorado Uranium Workers.” Computers in Biology and Medicine 13: 157-169.10.1016/S0010-4825(83)80011-0
Open DOI Search in Google Scholar Back to article
Newcombe, H. 1988. Handbook of Record Linkage. New-York: Oxford Medical Publications.
Search in Google Scholar Back to article
Särndal, C.-E., B. Swensson, and J. Wretman. 1992. Model Assisted Survey Sampling. New-York: Springer.10.1007/978-1-4612-4378-6
Search in Google Scholar Back to article
Schnell, R., T. Bachteler, and J. Reiher. 2009. “Privacy-Preserving Record Linkage using Bloom Filters”. BioMed Central Medical Informatics and Decision Making, 9.10.1186/1472-6947-9-41
Search in Google Scholar Back to article
Winkler, W.E. 1988. “Using the EM Algorithm for Weight Computation in the Fellegi-Sunter Model of Record Linkage”. In Proceedings of the Section on Survey Research Methods: American Statistical Association, August 22-25, 1988, New Orleans, Louisiana. 667-671.
Search in Google Scholar Back to article

Design-Based Estimation with Record-Linked Administrative Files and a Clerical Review Sample

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