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Activity Number: 603
Type: Topic Contributed
Date/Time: Thursday, August 2, 2012 : 8:30 AM to 10:20 AM
Sponsor: Section on Government Statistics
Abstract - #304446
Title: Application of Pattern-Mixture Models for Evaluation of Estimation Methods Under Responsive Designs
Author(s): Randall Powers*+ and John Eltinge
Companies: Bureau of Labor Statistics and Bureau of Labor Statistics
Address: 2 Massachusetts Ave., NE, Washington, DC, 20212, United States
Keywords: Cost-quality trade-offs ; Model identification informaton ; Nonresponse ; Paradata ; Pattern-mixture model ; Selection model
Abstract:

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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