A Practical Approach for Case Prioritization in A Panel Survey
Abstract Number:
2257
Submission Type:
Contributed Abstract
Contributed Abstract Type:
Speed
Participants:
Rui Jiao (1), Xiaoshu Zhu (1), Nicholas Askew (2), Ting Yan (1), Sylvia Dohrmann (1)
Institutions:
(1) Westat, N/A, (2) WESTAT, United States
Co-Author(s):
First Author:
Presenting Author:
Abstract Text:
Case prioritization has been employed by survey researchers as an adaptive survey design strategy to achieve optimal goals under fixed resources. One major use is to target the subgroups among low response propensity cases and prioritize them in the interviewers' workload without increasing data collection resources, to equalize response rates and to reduce nonresponse bias. Although existing research has shown the effectiveness of case prioritization, the approach of allocating the cases being prioritized in practical settings is not straightforward, especially in a dynamic case prioritization process. Tourangeau et al. (2017) provided a clear notion of what cases are the most worth pursuing. The authors recommended using a composited score with considerations of a case's response propensity, design weight, and its effect on the sample balance. Inspired by that research, this presentation provides a revised approach of identifying the most valuable cases in a panel survey setting with oversampling of subpopulations.
Keywords:
case prioritization|response propensity|dynamic adaptive design|nonresponse bias| |
Sponsors:
Survey Research Methods Section
Tracks:
Adaptive Design/Paradata
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