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<p>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.</p>
</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.

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

Journal of Official Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Respondent burden has important implications for survey outcomes, including response rates and attrition in panel surveys. Despite this, respondent burden...

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

Published Online: Dec 03, 2022

Page range: 1145 - 1175

Received: Feb 01, 2021

Accepted: Jul 01, 2022

DOI: https://doi.org/10.2478/jos-2022-0049

Keywords
Respondent burden measurement, response rates, panel surveys

© 2022 Morgan Earp et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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

Published Online: Dec 03, 2022

Page range: 1145 - 1175

Received: Feb 01, 2021

Accepted: Jul 01, 2022

DOI: https://doi.org/10.2478/jos-2022-0049

KeywordsRespondent burden measurement, response rates, panel surveys

© 2022 Morgan Earp et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
Respondent burden measurement, response rates, panel surveys