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

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 f...

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Bibliographic Details
Published in:Journal of official statistics Vol. 38; no. 4; pp. 1145 - 1175
Main Authors: Earp, Morgan, Kaplan, Robin, Toth, Daniell
Format: Journal Article
Language:English
Published: London, England SAGE Publications 01.12.2022
Sciendo
Statistics Sweden (SCB)
Subjects:
Employment
Exploratory factor analysis
Factor analysis
Marital status
Objectives
panel surveys
Polls & surveys
Regression analysis
Researcher subject relations
Respondent burden measurement
Response rates
Responses
response rates
Respondent burden measurement
panel surveys
ISSN:0282-423X, 2001-7367, 2001-7367
Online Access:Get full text
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Summary: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.
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ISSN:0282-423X
2001-7367
2001-7367
DOI:10.2478/jos-2022-0049