Improved Decision Rules In The Fellegi-Sunter Model Of Record Linkage

Improved Decision Rules In The Fellegi-Sunter Model Of Record Linkage (1993)

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by William E. Winkler

Venue:	Proceedings of the Section on Survey Research Methods, American Statistical Association
Citations:	29 - 12 self

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Datum	Value	Source
TITLE	Improved Decision Rules In The Fellegi-Sunter Model Of Record Linkage	user correction - Legacy Corrections
AUTHOR NAME	William E. Winkler	SVM HeaderParse 0.1
AUTHOR ADDR	Bureau of the Census, Washington, DC 20233-9100,	SVM HeaderParse 0.1
ABSTRACT	Many applications of the Fellegi-Sunter model use simplifying assumptions and ad hoc modifications to improve matching efficacy. Because of model misspecification, distinctive approaches developed in one application typically cannot be used in other applications and do not always make use of advances in statistical and computational theory. An ExpectationMaximization (EMH) algorithm that constrains the estimates to a convex subregion of the parameter space is given. The EMH algorithm provides probability estimates that yield better decision rules than unconstrained estimates. The algorithm is related to results of Meng and Rubin (1993) on Multi-Cycle Expectation-Conditional Maximization algorithms and make use of results of Haberman (1977) that hold for large classes of loglinear models. Key Words: MCECM Algorithm, Latent Class, Computer Matching, Error Rate This paper provides a theory for obtaining constrained maximum likelihood estimates for latent-class, loglinear models on finite ...	user correction - Legacy Corrections
YEAR	1993	INFERENCE
VENUE	Proceedings of the Section on Survey Research Methods, American Statistical Association	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	274--279	INFERENCE
TECH	Technical report	INFERENCE
CITATIONS	21 found	ParsCit 1.0