<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Providing an exact answer to open-ended numeric questions can be a burdensome task for respondents. Researchers often assume that adding an invitation to estimate (e.g., “Your best estimate is fine”) to these questions reduces cognitive burden, and in turn, reduces rates of undesirable response behaviors like item nonresponse, nonsubstantive answers, and answers that must be processed into a final response (e.g., qualified answers like “about 12” and ranges). Yet there is little research investigating this claim. Additionally, explicitly inviting estimation may lead respondents to round their answers, which may affect survey estimates. In this study, we investigate the effect of adding an invitation to estimate to 22 open-ended numeric questions in a mail survey and three questions in a separate telephone survey. Generally, we find that explicitly inviting estimation does not significantly change rates of item nonresponse, rounding, or qualified/range answers in either mode, though it does slightly reduce nonsubstantive answers for mail respondents. In the telephone survey, an invitation to estimate results in fewer conversational turns and shorter response times. Our results indicate that an invitation to estimate may simplify the interaction between interviewers and respondents in telephone surveys, and neither hurts nor helps data quality in mail surveys.</p>
</abstract>

Providing an exact answer to open-ended numeric questions can be a burdensome task for respondents. Researchers often assume that adding an invitation to estimate (e.g., “Your best estimate is fine”) to these questions reduces cognitive burden, and in turn, reduces rates of undesirable response behaviors like item nonresponse, nonsubstantive answers, and answers that must be processed into a final response (e.g., qualified answers like “about 12” and ranges). Yet there is little research investigating this claim. Additionally, explicitly inviting estimation may lead respondents to round their answers, which may affect survey estimates. In this study, we investigate the effect of adding an invitation to estimate to 22 open-ended numeric questions in a mail survey and three questions in a separate telephone survey. Generally, we find that explicitly inviting estimation does not significantly change rates of item nonresponse, rounding, or qualified/range answers in either mode, though it does slightly reduce nonsubstantive answers for mail respondents. In the telephone survey, an invitation to estimate results in fewer conversational turns and shorter response times. Our results indicate that an invitation to estimate may simplify the interaction between interviewers and respondents in telephone surveys, and neither hurts nor helps data quality in mail surveys.

Your Best Estimate is Fine. Or is It?

Journal of Official Statistics

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

{"article-title":"Your Best Estimate is Fine. Or is It?"}

Providing an exact answer to open-ended numeric questions can be a burdensome task for respondents. Researchers often assume that adding an invitation to...

Your Best Estimate is Fine. Or is It?

Published Online: Dec 03, 2022

Page range: 1097 - 1123

Received: Jan 01, 2021

Accepted: May 01, 2022

DOI: https://doi.org/10.2478/jos-2022-0047

Keywords
Estimation, enumeration, questionnaire design, data quality, respondent burden

© 2022 Jerry Timbrook et al., published by Sciendo

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

Your Best Estimate is Fine. Or is It?

Published Online: Dec 03, 2022

Page range: 1097 - 1123

Received: Jan 01, 2021

Accepted: May 01, 2022

DOI: https://doi.org/10.2478/jos-2022-0047

KeywordsEstimation, enumeration, questionnaire design, data quality, respondent burden

© 2022 Jerry Timbrook et al., published by Sciendo

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

Keywords
Estimation, enumeration, questionnaire design, data quality, respondent burden