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

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  • 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
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    References listed on IDEAS

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    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.
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    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].

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