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The Effects of Response Burden – Collecting Life History Data in a Self-Administered Mixed-Device Survey

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  • Carstensen Johann

    (German Centre for Higher Education Research and Science Studies, Lange Laube 12, 30159 Hannover, Germany.)

  • Lang Sebastian

    (German Centre for Higher Education Research and Science Studies, Lange Laube 12, 30159 Hannover, Germany.)

  • Cordua Fine

    (German Centre for Higher Education Research and Science Studies, Lange Laube 12, 30159 Hannover, Germany.)

Abstract

Collecting life history data is highly demanding and therefore prone to error since respondents must retrieve and provide extensive complex information. Research has shown that response burden is an important factor influencing data quality. We examine whether increases in different measures of response burden in a (mixed-device) online survey lead to adverse effects on the data quality and whether these effects vary by the type of device used (mobile versus non-mobile). We conducted an experimental study in an online mixed-device survey, for which we developed a questionnaire on the educational and occupational trajectories of secondary-school graduates, undergraduates, and university graduates. To address our research question, we randomly assigned different levels of response burden to the participants and compared different measures on the data quality and response. We found mixed evidence for unfavourable effects of response burden on the examined outcomes. While some of our results were expected, they were not consistent across all subgroups. Most interestingly, the effects of response burden on outcomes seemed to differ based on the device used. Hence, we conclude that further research is needed to optimise the collection of complex data from different groups of participants.

Suggested Citation

  • Carstensen Johann & Lang Sebastian & Cordua Fine, 2022. "The Effects of Response Burden – Collecting Life History Data in a Self-Administered Mixed-Device Survey," Journal of Official Statistics, Sciendo, vol. 38(4), pages 1069-1095, December.
    • Handle: RePEc:vrs:offsta:v:38:y:2022:i:4:p:1069-1095:n:15
    DOI: 10.2478/jos-2022-0046
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    References listed on IDEAS

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    3. Papke, Leslie E & Wooldridge, Jeffrey M, 1996. "Econometric Methods for Fractional Response Variables with an Application to 401(K) Plan Participation Rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(6), pages 619-632, Nov.-Dec..
    4. Mick P. Couper & Frauke Kreuter, 2013. "Using paradata to explore item level response times in surveys," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(1), pages 271-286, January.
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