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Activity Number:
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352
- Small Area Estimation, Analysis of Complex Sample Survey Data, and New Advances for Health Surveys
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Type:
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Contributed
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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 #317887
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Title:
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A General Stopping Rule for Survey Data Collection
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Author(s):
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Xinyu Zhang* and James Wagner and Michael R. Elliott and Brady T. West and Stephanie Coffey
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Companies:
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University of Michigan - Ann Anbor and University of Michigan and University of Michigan and University of Michigan and U.S. Census Bureau
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Keywords:
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Stopping rule;
Responsive survey design;
Nonresponse bias
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Abstract:
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Surveys are experiencing declining response rates. With more and more effort expended to combat these declining response rates, the cost of large-scale surveys has continued to rise. Recent technological developments in survey data collection have allowed the survey designer to make near-real-time intervention decisions for particular subsets of the sample. Stopping rules are one of the interventions often considered to improve the efficiency of data collection. Stopping some cases essentially reallocates effort from stopped cases to others, but most previously proposed stopping rules have only considered single estimates. In multipurpose surveys, there may be data quality objectives that must be met for multiple estimates with constraints on costs. We introduce a stopping rule that accounts for the cost and the quality of one or more estimates. The proposed stopping rule is illustrated via simulation using data from the Health and Retirement Study.
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Authors who are presenting talks have a * after their name.
