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Abstract Details
Activity Number:
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603
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Type:
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Topic Contributed
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Date/Time:
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Thursday, August 2, 2012 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Government Statistics
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Abstract - #304446 |
Title:
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Application of Pattern-Mixture Models for Evaluation of Estimation Methods Under Responsive Designs
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Author(s):
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Randall Powers*+ and John Eltinge
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Companies:
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Bureau of Labor Statistics and Bureau of Labor Statistics
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Address:
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2 Massachusetts Ave., NE, Washington, DC, 20212, United States
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Keywords:
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Cost-quality trade-offs ;
Model identification informaton ;
Nonresponse ;
Paradata ;
Pattern-mixture model ;
Selection model
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Abstract:
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In work with data collected under a responsive design, most analytic approaches may be viewed as extensions of methods developed previously under, respectively, selection models or pattern-mixture models for nonresponse. Under selection models, one approximates the probability of specified responses (or, more generally, the probability of observing certain profiles of paradata) as a function of observable information from frame data, survey data and paradata. Under pattern-mixture models, one views the moment structure of observed survey data as functions of specified response patterns (or, more generally, specified patterns of observed paradata). For the pattern-mixture approach, an especially important issue is the use of constraints on subpopulation moments to ensure that the resulting models are estimable from available data.
Following a brief review of these concepts, this paper presents some simulation-based evaluations of the properties of the estimators based on the pattern-mixture approach. Special attention is directed toward evaluation of these properties under moderate deviations from assumed conditions.
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