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Combatting Attrition Bias Using Case Prioritization in the Survey of Income and Program Participation
Stephanie Coffey
U.S. Census Bureau
Jason Fields
U.S. Census Bureau
Amanda Nagle
U.S. Census Bureau
Kevin Tolliver
U.S. Census Bureau
This paper details an experiment testing an adaptive survey design approach to improving sample representativeness in a national longitudinal face-to-face survey. The adaptive strategy, case prioritization, was employed to focus data collection resources on cases that we feel may have the highest impact on attrition bias in the Survey of Income and Program Participation. Achieving interviews with these cases can have an impact on estimates of program participation, the essential aim of the survey. The findings of the experiment suggest that prioritizing cases can help the survey retain these targeted cases.