IDEAS home Printed from https://ideas.repec.org/a/sae/somere/v43y2014i3p452-464.html
   My bibliography  Save this article

A Note on Mechanisms Leading to Lower Data Quality of Late or Reluctant Respondents

Author

Listed:
  • Frauke Kreuter
  • Gerrit Müller
  • Mark Trappmann

Abstract

Survey methodologists worry about trade-offs between nonresponse and measurement error. Past findings indicate that respondents brought into the survey late provide low-quality data. The diminished data quality is often attributed to lack of motivation. Quality is often measured through internal indicators and rarely through true scores. Using administrative data for validation purposes, this article documents increased measurement error as a function of recruitment effort for a large-scale employment survey in Germany. In this case study, the reduction in measurement quality of an important target variable is largely caused by differential measurement error in subpopulations and respective shifts in sample composition, as well as increased cognitive burden through the increased length of recall periods among later respondents. Only small portions of the relationship could be attributed to a lack of motivation among late or reluctant respondents.

Suggested Citation

  • Frauke Kreuter & Gerrit Müller & Mark Trappmann, 2014. "A Note on Mechanisms Leading to Lower Data Quality of Late or Reluctant Respondents," Sociological Methods & Research, , vol. 43(3), pages 452-464, August.
    • Handle: RePEc:sae:somere:v:43:y:2014:i:3:p:452-464
    DOI: 10.1177/0049124113508094
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0049124113508094
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0049124113508094?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Katharine G. Abraham & Aaron Maitland & Suzanne M. Bianchi, 2006. "Non-response in the American Time Use Survey: Who Is Missing from the Data and How Much Does It Matter?," NBER Technical Working Papers 0328, National Bureau of Economic Research, Inc.
    2. Bollinger, Christopher R & David, Martin H, 2001. "Estimation with Response Error and Nonresponse: Food-Stamp Participation in the SIPP," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(2), pages 129-141, April.
    3. Kristen Olson, 2013. "Do non-response follow-ups improve or reduce data quality?: a review of the existing literature," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(1), pages 129-145, January.
    4. Mark Trappman & Stefanie Gundert & Claudia Wenzig & Daniel Gebhardt, 2010. "PASS – A Household Panel Survey for Research on Unemployment and Poverty," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 130(4), pages 609-622.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. John L. Czajka & Amy Beyler, "undated". "Declining Response Rates in Federal Surveys: Trends and Implications (Background Paper)," Mathematica Policy Research Reports a714f76e878f4a74a6ad9f15d, Mathematica Policy Research.
    2. Berg, Marco & Cramer, Ralph & Dickmann, Christian & Gilberg, Reiner & Jesske, Birgit & Kleudgen, Martin & Beste, Jonas & Dummert, Sandra & Frodermann, Corinna & Fuchs, Benjamin & Schwarz, Stefan & Tra, 2018. "Codebuch und Dokumentation des Panel 'Arbeitsmarkt und soziale Sicherung' (PASS) : Datenreport Welle 11," FDZ Datenreport. Documentation on Labour Market Data 201806_de, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bruckmeier, Kerstin & Riphahn, Regina T. & Wiemers, Jürgen, 2019. "Benefit underreporting in survey data and its consequences for measuring non-take-up: new evidence from linked administrative and survey data," IAB-Discussion Paper 201906, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    2. Felderer Barbara & Kirchner Antje & Kreuter Frauke, 2019. "The Effect of Survey Mode on Data Quality: Disentangling Nonresponse and Measurement Error Bias," Journal of Official Statistics, Sciendo, vol. 35(1), pages 93-115, March.
    3. Meyer, Bruce D. & Mittag, Nikolas, 2021. "An empirical total survey error decomposition using data combination," Journal of Econometrics, Elsevier, vol. 224(2), pages 286-305.
    4. Kerstin Bruckmeier & Katrin Hohmeyer & Stefan Schwarz, 2018. "Welfare receipt misreporting in survey data and its consequences for state dependence estimates: new insights from linked administrative and survey data," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 52(1), pages 1-21, December.
    5. Michael Osei Mireku & Alina Rodriguez, 2021. "Sleep Duration and Waking Activities in Relation to the National Sleep Foundation’s Recommendations: An Analysis of US Population Sleep Patterns from 2015 to 2017," IJERPH, MDPI, vol. 18(11), pages 1-15, June.
    6. Joshua Graff Zivin & Matthew Neidell, 2014. "Temperature and the Allocation of Time: Implications for Climate Change," Journal of Labor Economics, University of Chicago Press, vol. 32(1), pages 1-26.
    7. Gürtzgen, Nicole & (né Nolte), André Diegmann & Pohlan, Laura & van den Berg, Gerard J., 2021. "Do digital information technologies help unemployed job seekers find a job? Evidence from the broadband internet expansion in Germany," European Economic Review, Elsevier, vol. 132(C).
    8. Craig Gundersen & Brent Kreider, 2008. "Food Stamps and Food Insecurity: What Can Be Learned in the Presence of Nonclassical Measurement Error?," Journal of Human Resources, University of Wisconsin Press, vol. 43(2), pages 352-382.
    9. Meyer, Bruce D. & Mittag, Nikolas, 2019. "Combining Administrative and Survey Data to Improve Income Measurement," IZA Discussion Papers 12266, Institute of Labor Economics (IZA).
    10. Adrian Chadi, 2019. "Dissatisfied with life or with being interviewed? Happiness and the motivation to participate in a survey," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 53(3), pages 519-553, October.
    11. repec:iab:iabfda:201307(en is not listed on IDEAS
    12. Roberts Caroline & Vandenplas Caroline & Herzing Jessica M.E., 2020. "A Validation of R-Indicators as a Measure of the Risk of Bias using Data from a Nonresponse Follow-Up Survey," Journal of Official Statistics, Sciendo, vol. 36(3), pages 675-701, September.
    13. Andreas Damelang & Georgi Kloß, 2013. "Poverty and the social participation of young people—an analysis of poverty-related withdrawal mechanisms [Armut und soziale Teilhabe von Kindern und Jugendlichen – Eine Analyse armutsspezifischer ," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 46(4), pages 321-333, December.
    14. Daniel S. Hamermesh & Katie R. Genadek & Michael C. Burda, 2022. "Reply to “Racial Differences in Time at Work Not Working†by William A. Darity Jr. et al," ILR Review, Cornell University, ILR School, vol. 75(3), pages 573-577, May.
    15. Jens Bonke & Mette Deding & Mette Lausten & Leslie S. Stratton, 2008. "Intra‐Household Specialization in Housework in the United States and Denmark," Social Science Quarterly, Southwestern Social Science Association, vol. 89(4), pages 1023-1043, December.
    16. Arenas-Arroyo, Esther & Schmidpeter, Bernhard, 2022. "Spillover effects of immigration policies on children's human capital," Ruhr Economic Papers 974, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    17. Karen S Hamrick & Margaret Andrews, 2016. "SNAP Participants’ Eating Patterns over the Benefit Month: A Time Use Perspective," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-18, July.
    18. Alho, Juha & Müller, Gerrit & Pflieger, Verena & Rendtel, Ulrich, 2017. "The fade away of an initial bias in longitudinal surveys," Discussion Papers 2017/25, Free University Berlin, School of Business & Economics.
    19. Borgschulte, Mark & Cho, Heepyung & Lubotsky, Darren, 2022. "Partisanship and survey refusal," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 332-357.
    20. Markus Frölich & Martin Huber, 2014. "Treatment Evaluation With Multiple Outcome Periods Under Endogeneity and Attrition," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(508), pages 1697-1711, December.
    21. Vogel, Dominik, 2018. "Vogel (2018): Matching survey responses with anonymity in environments with privacy concerns: A practical guide," SocArXiv nwjd7, Center for Open Science.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:somere:v:43:y:2014:i:3:p:452-464. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.