Modeling the Relationship between Proxy Measures of Respondent Burden and Survey Response Rates in a Household Panel Survey

Earp Morgan (), Kaplan Robin () and Toth Daniell ()
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Earp Morgan: U.S. Centers for Disease Control and Prevention, National Center for Health Statistics, Division of Research and Methodology, 3311 Toledo Rd, Hyattsville, MD, 20782, U.S.A.
Kaplan Robin: U.S. Bureau of Labor Statistics, Office of Survey Methods Research, Suite 5930. 2 Massachusetts Ave NE, Washington, DC 20212, U.S.A.
Toth Daniell: U.S. Bureau of Labor Statistics, Office of Survey Methods Research, Suite 5930. 2 Massachusetts Ave NE, Washington, DC 20212, U.S.A.

Journal of Official Statistics, 2022, vol. 38, issue 4, 1145-1175

Abstract: Respondent burden has important implications for survey outcomes, including response rates and attrition in panel surveys. Despite this, respondent burden remains an understudied topic in the field of survey methodology, with few researchers systematically measuring objective and subjective burden factors in surveys used to produce official statistics. This research was designed to assess the impact of proxy measures of respondent burden, drawing on both objective (survey length and frequency), and subjective (effort, saliency, and sensitivity) burden measures on response rates over time in the Current Population Survey (CPS). Exploratory Factor Analysis confirmed the burden proxy measures were interrelated and formed five distinct factors. Regression tree models further indicated that both objective and subjective proxy burden factors were predictive of future CPS response rates. Additionally, respondent characteristics, including employment and marital status, interacted with these burden factors to further help predict response rates over time. We discuss the implications of these findings, including the importance of measuring both objective and subjective burden factors in production surveys. Our findings support a growing body of research suggesting that subjective burden and individual respondent characteristics should be incorporated into conceptual definitions of respondent burden and have implications for adaptive design.

Keywords: Respondent burden measurement; response rates; panel surveys (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:offsta:v:38:y:2022:i:4:p:1145-1175:n:10

DOI: 10.2478/jos-2022-0049

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