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Activity Number:
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326
- Recent Developments in Probabilistic Record Linkage, Multiple Systems Estimation, and Entity Resolution
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Type:
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Invited
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Date/Time:
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Thursday, August 12, 2021 : 10:00 AM to 11:50 AM
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Sponsor:
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Survey Research Methods Section
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Abstract #316599
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Title:
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A Theoretical Framework for Probabilistic Record Linkage in Multiple-Frame Surveys
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Author(s):
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Takumi Saegusa* and Partha Lahiri
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Companies:
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University of Maryland, College Park and University of Maryland, College Park
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Keywords:
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domain membership;
multiple-frame survey;
record linkage
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Abstract:
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There is a growing interest in using multiple-frame surveys in recent years in order to save survey costs and reduce different types of nonsampling errors. Following the pioneering work by Hartley, methods and theories have been developed. A key underlying assumption of current papers on multiple-frame surveys is known domain membership of each unit of the finite population. But this assumption is hardly met in practice. The effect of violation of this critical assumption on finite population inference is not fully understood. We first investigate the effect of misspecification of the domain membership on estimation and variance estimation. We then exploit the recent development of probabilistic record linkage techniques in adjusting for biases due to domain membership misspecification in the finite population inference. We study the properties of the proposed estimators and the associated variance estimators analytically and through Monte Carlo simulations.
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Authors who are presenting talks have a * after their name.
