Course number: ADRCE-training001 Shlomo
Summary of Course:
The course will introduce basic concepts and methods of record linkage and will cover methodological and statistical aspects of this new emerging area. The course will provide theory and practical applications of deterministic and probabilistic approaches to record linkage including pre-matching processes, matching weights, types of errors in classification, evaluation of the quality of linkage procedures, implementation of the E-M algorithm and an introduction to the analysis of linked datasets. By the end of the course, participants should have an understanding of record linkage techniques and be able to implement and evaluate record linkage procedures. The course does not assume any prior knowledge of record linkage and there will be a session devoted to the revision of basic concepts in probability theory necessary to understand probabilistic record linkage. The course will have a strong practical emphasis and will include tutorials and a computer workshop to enable course participants to put the taught methods into practice. The software that will be used is SAS although no familiarity with SAS prior to the course is required. (This course is a more intensive course than the course ‘Introduction to Data Linkage').
Course Objectives:
Target Audience:
The course is aimed at researchers who need to gain an understanding of record linkage techniques. The course emphasizes putting theory into practice for those who need to carry out record linkage in their own work. Participants may be academic researchers in the social and health sciences or may work in government, survey agencies, official statistics, for charities or the private sector.
Thanks to continued ESRC funding we are able to offer this course at reduced rates as follows:
The course fee includes course materials, lunches and morning and afternoon refreshments. Travel and accommodation are to be arranged and paid for by the participant.
Location and Accommodation:
The course will be held at the Southampton Statistical Sciences Research Institute, Building 39, University of Southampton, Southampton, SO17 1BJ. Participants are left to make their own accommodation arrangements. Further information on local accommodation and course location is available on the
CASS website
.
Duration:
The course will start with registration and coffee at 9.45 with formal teaching starting at 10.00 am on the first day (and on all subsequent days). The lectures will go to 17:00. On the last day, there will be an opportunity for participants to ask questions on how to link their own datasets (you can bring your own data to the course if you wish).
Pre-requisite:
The course does not assume any prior knowledge of record linkage and a special session will be devoted to the revision of probability theory necessary to understanding probabilistic record linkage. No familiarity with the software SAS will be assumed.
Course Material:
Participants will receive course notes, tutorials and computing lab material.
The Instructor:
Natalie Shlomo is a Professor in Social Statistics, School of Social Sciences at the University of Manchester. She has extensive knowledge of survey methods including data processing: record linkage, edit and imputation processes and statistical disclosure control.
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Fellegi, I. P. and Sunter, A. B. (1969) A Theory for Record Linkage , Journal of the American Statistical Association, 64, 1183-1210.
Gill, L. (2001) Methods for Automatic Record Matching and Linkage and their use in National Statistics , The National Statistics Methodology Series, ONS (available at http://www.ons.gov.uk/ons/guide-method/method-quality/specific/gss-methodology-series/index.html )
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, Survey Methodology, 19, 39-58
http://www.fcsm.gov/working-papers/scheuren_part1.pdf
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Regression Analysis of Data Files that are Computer Matched II
, Survey Methodology, 23, 157-165
http://www.fcsm.gov/working-papers/scheuren_part2.pdf
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, New York: J. Wiley, 355-384
http://www.fcsm.gov/working-papers/wwinkler.pdf
Record Linkage References
William.E.Winker@census.gov
(2008Mar01)
http://www.hcp.med.harvard.edu/statistics/survey-soft/docs/WinklerReclinkRef.pdf