Identifying Likely Duplicates by Record Linkage in a Survey of Prostitutes

Thomas R Belin; Hemant Ishwaran; Naihua Duan; Sandra H Berry; David E Kanouse

doi:10.1002/0470090456.ch29

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Identifying Likely Duplicates by Record Linkage in a Survey of Prostitutes

Thomas R Belin, Hemant Ishwaran, Naihua Duan, Sandra H Berry and David E Kanouse

Applied Bayesian Modeling and Causal Inference from Incomplete‐Data Perspectives, pp.319-329

John Wiley & Sons, Ltd

2004-07-23

DOI: https://doi.org/10.1002/0470090456.ch29

Abstract

probabilities of duplication

mixture‐model framework

potential systematic relationship

distance metric

testing framework

mixture components estimation

Los Angeles Women's Health Risk Study (LAWHRS)

This chapter contains sections titled: Concern about duplicates in an anonymous survey General frameworks for record linkage Estimating probabilities of duplication in the Los Angeles Women's Health Risk Study Discussion

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Title: Identifying Likely Duplicates by Record Linkage in a Survey of Prostitutes
Creators: Thomas R Belin
Hemant Ishwaran
Naihua Duan
Sandra H Berry
David E Kanouse - RAND Corporation, Santa Monica, Calif., USA
Contributors: Andrew Gelman (Editor) - Department of Statistics and Department of Political Science, Columbia University, New York, USA
Xiao‐Li Meng (Editor) - Department of Statistics, Harvard University, USA
Publication Details: Applied Bayesian Modeling and Causal Inference from Incomplete‐Data Perspectives, pp.319-329
Publisher: John Wiley & Sons, Ltd; Chichester, UK
Number of pages: 11
Academic Unit: Miller School of Medicine; UMMG Department of Public Health Sciences Research
Language: English
Resource Type: Book chapter
Record Identifier: 991031598324202976