Skip to main content
SpringerLink
Log in

Linking Surveys with Big Data

Issues of Consent

  • Chapter
  • First Online:
Qualität bei zusammengeführten Daten

Zusammenfassung

Sample surveys are ubiquitously used in the academic, government, and commercial sectors to gain insights about diverse populations. The efficiency of surveys, particularly those that are based on random samples, is in their ability to make robust inferences about a population without needing to interview every single member of that population. The possible inferences extend to all data that is collected during the survey interview, regardless of how many questions are asked of the respondents.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 49.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Literatur

  • Bates, N., Wroblewski, M. J., & Pascale, J. (2012). Public Attitudes Toward the Use of Administrative Records in the U.S. Census: Does Question Frame Matter? Technical Report, Survey Methodology Series #2012-04, United States Census Bureau.

    Google Scholar 

  • Christen, P. (2012). Data Matching: Concepts and Techniques for Record Linkage, Entity Resolution, and Duplicate Detection. Springer.

    Google Scholar 

  • da Silva, M. E. M., Coeli, C. M., Ventura, M., Palacios, M., Magnanini, M. M. F., Camargo, T. M. C. R., & Camargo, K. R. (2012). Informed Consent for Record Linkage: a Systematic Review. Journal of Medical Ethics, 38(10), 639-642.

    Google Scholar 

  • Das, M., & Couper, M. P. (2014). Optimizing Opt-Out Consent for Record Linkage. Journal of Official Statistics, 30(3), 479-497.

    Google Scholar 

  • D’Orazio, M., Di Zio, M., & Scanu, M. (2006). Statistical Matching: Theory and Practice. Wiley.

    Google Scholar 

  • Fulton, J. A. (2012). Respondent Consent to Use Administrative Data. Unpublished Doctoral Dissertation, University of Maryland.

    Google Scholar 

  • Gessendorfer, J., Beste, J., Drechsler, J., & Sakshaug, J. W. (2018). Statistical Matching as a Supplement to Record Linkage: A Valuable Method to Tackle Nonconsent Bias?. Journal of Official Statistics, 34(4), 909-933.

    Google Scholar 

  • Herzog, T. N., Scheuren, F. J., & Winkler, W. E. (2007). Data Quality and Record Linkage Techniques. Springer.

    Google Scholar 

  • Jäckle, A., Beninger, K., Burton, J., & Couper, M.P. (2018). Understanding Data Linkage Consent in Longitudinal Surveys. Understanding Society Working Paper Series, No. 2018-07.

    Google Scholar 

  • Jenkins, S. P., Cappellari, L., Lynn, P., Jäckle, A., & Sala, E. (2006). Patterns of Consent: Evidence from a General Household Survey. Journal of the Royal Statistical Society: Series A (Statistics in Society), 169(4), 701-722.

    Google Scholar 

  • Knies, G., & Burton, J. (2014). Analysis of Four Studies in a Comparative Framework Reveals: Health Linkage Consent Rates on British Cohort Studies Higher than on UK Household Panel Surveys. BMC Medical Research Methodology, 14(1), 125.

    Google Scholar 

  • Kreuter, F., Haas, G. C., Keusch, F., Bähr, S., & Trappmann, M. (2018). Collecting Survey and Smartphone Sensor Data with an App: Opportunities and Challenges Around Privacy and Informed Consent. Social Science Computer Review, advance online access.

    Google Scholar 

  • Kreuter, F., Sakshaug, J. W., & Tourangeau, R. (2016). The Framing of the Record Linkage Consent Question. International Journal of Public Opinion Research, 28(1), 142-152.

    Google Scholar 

  • Little, R.J.A. (1986). Survey Nonresponse Adjustments for Estimates of Means. International Statistical Review, 54(2), 139–157.

    Google Scholar 

  • Pascale, J. (2011). Requesting Consent to Link Survey Data to Administrative Records: Results from a Split-Ballot Experiment in the Survey of Health Insurance and Program Participation (SHIPP). Study Series Survey Methodology 2011-03. U.S. Census Bureau.

    Google Scholar 

  • Sakshaug, J. W., & Antoni, M. (2017). Errors in Linking Survey and Administrative Data. P. Biemer, E. de Leeuw, S. Eckman, B. Edwards, F. Kreuter, L. Lyberg, N.C. Tucker, B. West (eds.), Total Survey Error in Practice (pp. 557-573). Wiley.

    Google Scholar 

  • Sakshaug, J. W., & Huber, M. (2016). An Evaluation of Panel Nonresponse and Linkage Consent Bias in a Survey of Employees in Germany. Journal of Survey Statistics and Methodology, 4(1), 71-93.

    Google Scholar 

  • Sakshaug, J. W., & Kreuter, F. (2012). Assessing the Magnitude of Non-Consent Biases in Linked Survey and Administrative Data. Survey Research Methods, 6(2), 113-122.

    Google Scholar 

  • Sakshaug, J. W., & Kreuter, F. (2014). The Effect of Benefit Wording on Consent to Link Survey and Administrative Records in a Web Survey. . Public Opinion Quarterly, 78(1), 166-176.

    Google Scholar 

  • Sakshaug, J. W., & Vicari, B. J. (2017). Obtaining Record Linkage Consent from Establishments: The Impact of Question Placement on Consent Rates and Bias. Journal of Survey Statistics and Methodology, 6(1), 46-71.

    Google Scholar 

  • Sakshaug, J. W., Couper, M. P., Ofstedal, M. B., & Weir, D. R. (2012). Linking Survey and Administrative Records: Mechanisms of Consent. Sociological Methods & Research, 41(4), 535-569.

    Google Scholar 

  • Sakshaug, J. W., Hülle, S., Schmucker, A., & Liebig, S. (2017). Exploring the Effects of Interviewer-and Self-Administered Survey Modes on Record Linkage Consent Rates and Bias. Survey Research Methods, 11(2), 171-188.

    Google Scholar 

  • Sakshaug, J. W., Schmucker, A., Kreuter, F., Couper, M. P., & Singer, E. (2019). The Effect of Framing and Placement on Linkage Consent. Public Opinion Quarterly, 83(S1), 289-308.

    Google Scholar 

  • Sakshaug, J. W., Wolter, S., & Kreuter, F. (2015). Obtaining Record Linkage Consent: Results from a Wording Experiment in Germany. Survey Methods: Insights from the Field, 12.

    Google Scholar 

  • Sakshaug, J., Tutz, V., & Kreuter, F. (2013). Placement, Wording, and Interviewers: Identifying Correlates of Consent to Link Survey and Administrative data. Survey Research Methods, 7(2), 133-144.

    Google Scholar 

  • Sala, E., Burton, J., & Knies, G. (2012). Correlates of Obtaining Informed Consent to Data Linkage: Respondent, Interview, and Interviewer Characteristics. Sociological Methods & Research, 41(3), 414-439.

    Google Scholar 

  • Sala, E., Knies, G., & Burton, J. (2014). Propensity to Consent to Data Linkage: Experimental Evidence on the Role of Three Survey Design Features in a UK Longitudinal Panel. International Journal of Social Research Methodology, 17(5), 455-473.

    Google Scholar 

  • Thornby, M., Calderwood, L., Kotecha, M., Beninger, K., & Gaia, A. (2018). Collecting Multiple Data Linkage Consents in a Mixed-mode Survey: Evidence from a large-scale longitudinal study in the UK. Survey Methods: Insights from the Field, 14.

    Google Scholar 

  • Yang, D., Fricker, S., & Eltinge, J. (2017). Methods for Exploratory Assessment of Consent-to-Link in a Household Survey. Journal of Survey Statistics and Methodology, 7(1), 118-155.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institut für Arbeitsmarkt- und Berufsforschung (IAB) der Bundesagentur für Arbeit (BA), Regensburger, Nürnberg, Deutschland

    Joseph W. Sakshaug

Authors
  1. Joseph W. Sakshaug
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Joseph W. Sakshaug .

Editor information

Editors and Affiliations

  1. ADM Arbeitskreis Deutscher Markt-und Sozialforschungsinstitute eV, Berlin, Germany

    Bettina Klumpe

  2. GESIS – Leibniz-Institut für Sozialwissenschaften, Mannheim, Germany

    Jette Schröder

  3. Statistisches Bundesamt, Wiesbaden, Hessen, Germany

    Markus Zwick

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Der/die Herausgeber bzw. der/die Autor(en), exklusiv lizenziert durch Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Sakshaug, J.W. (2020). Linking Surveys with Big Data. In: Klumpe, B., Schröder, J., Zwick, M. (eds) Qualität bei zusammengeführten Daten. Schriftenreihe der ASI - Arbeitsgemeinschaft Sozialwissenschaftlicher Institute. Springer VS, Wiesbaden. https://doi.org/10.1007/978-3-658-31009-7_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-658-31009-7_12

  • Published:

  • Publisher Name: Springer VS, Wiesbaden

  • Print ISBN: 978-3-658-31008-0

  • Online ISBN: 978-3-658-31009-7

  • eBook Packages: Social Science and Law (German Language)

Publish with us

Policies and ethics

Search

Navigation