Ackermann-Piek, Daniela

Blohm, Michael

Edwards, Brad

Gummer, Tobias

Meitinger, Katharina

Silber, Henning

English

SSOAR - Social Science Open Access Repository 

www.ssoar.infoFieldwork Monitoring Strategies for Interviewer-Administered SurveysMeitinger, Katharina; Ackermann-Piek, Daniela; Blohm, Michael; Edwards,Brad; Gummer, Tobias; Silber, HenningVeröffentlichungsversion / Published VersionZeitschriftenartikel / journal articleZur Verfügung gestellt in Kooperation mit / provided in cooperation with:GESIS - Leibniz-Institut für SozialwissenschaftenEmpfohlene Zitierung / Suggested Citation:Meitinger, K., Ackermann-Piek, D., Blohm, M., Edwards, B., Gummer, T., & Silber, H. (2020). FieldworkMonitoring Strategies for Interviewer-Administered Surveys. Survey Methods: Insights from the Field, 1-4. https://doi.org/10.13094/SMIF-2020-00007Nutzungsbedingungen:Dieser Text wird unter einer CC BY Lizenz (Namensnennung) zurVerfügung gestellt. Nähere Auskünfte zu den CC-Lizenzen findenSie hier:https://creativecommons.org/licenses/by/4.0/deed.deTerms of use:This document is made available under a CC BY Licence(Attribution). For more Information see:https://creativecommons.org/licenses/by/4.020.05.20 07:45Fieldwork Monitoring Strategies for Interviewer-Administered Surveys | Survey Methods: Insights from the Field (SMIF)Page 1 sur 4https://surveyinsights.org/?p=13732&preview_id=13732Fieldwork Monitoring Strategies for Interviewer-AdministeredSurveysKatharina Meitinger, Utrecht University, The NetherlandsDaniela Ackermann-Piek, GESIS – Leibniz Institute for the Social Sciences, GermanyMichael Blohm, GESIS – Leibniz Institute for the Social Sciences, GermanyBrad Edwards, Westat, United StatesTobias Gummer, GESIS – Leibniz Institute for the Social Sciences, GermanyHenning Silber, GESIS – Leibniz Institute for the Social Sciences, Germany18.05.2020How to cite this article: Meitinger K., Ackermann-Piek, D., Blohm M., Edwards B., Gummer T. &Silber H. (2020). Fieldwork Monitoring Strategies for Interviewer-Administered Surveys. SurveyMethods: Insights from the Field. Special issue: ‘Fieldword Monitoring Strategies for Interviewer-Administered Surveys’. Retrieved from https://surveyinsights.org/?p=13732    DOI:10.13094/SMIF-2020-00007Copyright© the authors 2020. This work is licensed under a Creative Commons Attribution 4.0 InternationalLicense (CC BY 4.0) Copyright© the authors 2020. This work is licensed under a Creative Commons Attribution 4.0 InternationalLicense (CC BY 4.0) Fieldwork monitoring is essential during the data collection of surveys to ensure high-quality data(Koch, et al., 2009; Lyberg & Biemer, 2008; Lynn, 2003; Malter, 2014). During the data collectionperiod, the continuous evaluation of performance indicators (Edwards, Maitland, & Connor, 2017;Schouten, Sholmo, & Skinner, 2011; Schouten et al., 2012) such as response rates, risk ofnonresponse bias, contact attempts, or fieldwork intensity per sampling point and interviewer,provides the possibility to detect data collection issues at an early stage and to react timely withtargeted interventions to tackle these issues. In this regard, adaptive and responsive surveydesigns (Groves & Heeringa, 2006; Wagner, 2008; Schouten, Peytchev, & Wagner, 2018) havereceived increasing attention by survey researchers.A large variety of performance indicators are available and there are many opportunities tointervene if any issues are detected during the data collection phase (Kreuter, 2013). Dependingon the specific survey context, some indicators might be more useful to monitor than others. Also,the optimal monitoring frequency for indicators may differ depending on the specific setting of asurvey. An important distinction regarding optimal fieldwork monitoring strategies is whether thesurvey is conducted by the research organization itself or whether a commercial survey agency iscontracted to field the survey. In the latter case, some indicators might be less informative becausethe performance indicators are usually not delivered to the research organization on a daily basis,and field interventions need more time to be implemented successfully.20.05.20 07:45Fieldwork Monitoring Strategies for Interviewer-Administered Surveys | Survey Methods: Insights from the Field (SMIF)Page 2 sur 4https://surveyinsights.org/?p=13732&preview_id=13732This special issue spotlights the lessons learned when working with different fieldwork monitoringstrategies in various settings. In particular, the topics of interest include which performanceindicators have been implemented successfully (e.g., to reduce errors described in the TotalSurvey Error framework, see Groves & Lyberg, 2010) and which have been deemed to be lessuseful. The large variety of indicators is paralleled by a multitude of possible fieldwork measures orinterventions that address specific aspects of the data collection process (e.g., change or re-training of interviewers, re-contact of soft refusals, tailored reminder letters or adjustment ofincentives). Many large scale-survey programs have an abundance of experiences regarding theefficiency and effectiveness of different fieldwork monitoring strategies. Due to the oftennonexperimental nature of many field activities, articles sharing this expertise are rare. This specialissue provides a platform to share this valuable best practice knowledge and provide insights onwhich fieldwork strategies and tools are employed in the field.Altogether, seven contributions are included in this special issue. The study by Meitinger et al.provides a descriptive overview and relevance rating of fieldwork indicators and measures that arecurrently being used by seventeen large-scale surveys in Germany. Five articles provide casestudies from specific national and international survey programs. Briceno-Rosas, Butt, andKappelhof describe the fieldwork management system of the European Social Survey. Cornessediscusses the utility of auxiliary data with the example of the German Internet Panel. Martin andZabal illustrate a responsive design approach, developing classification trees for auxiliary data tomodel and predict classes of nonrespondents with the fieldwork procedures of PIAAC Germany2012. Bergmann and Scherpenzeel provide insights into the field monitoring strategies of theSurvey of Health, Ageing and Retirement in Europe and focus the implementation ofadaptive/responsive survey design and its effects on sample representativeness. Calderwood etal. share their experiences in the UK Millennium Cohort Study by comparing differences in thefieldwork monitoring procedures across waves. In the final contribution, Bieber et al. illustrate thepotential of visualization of geospatial data for fieldwork monitoring in the context of the GermanLongitudinal Election Study.An overview of the contributions by authors’ names, title, methodological focus, survey,and country20.05.20 07:45Fieldwork Monitoring Strategies for Interviewer-Administered Surveys | Survey Methods: Insights from the Field (SMIF)Page 3 sur 4https://surveyinsights.org/?p=13732&preview_id=13732 References1. Edwards, B., Maitland, A., & Connor, S. (2017). Measurement Error in Survey OperationsManagement: Detection, Quantification, Visualization, and Reduction. In P. Biemer, E.D. deLeeuw, S. Eckman, B. Edwards, F. Kreuter, L. Lyberg, N.C. Tucker, and B.T. West (Eds.):Total Survey Error in Practice (pp.255-278). Hoboken, New Jersey: John Wiley & Sons.20.05.20 07:45Fieldwork Monitoring Strategies for Interviewer-Administered Surveys | Survey Methods: Insights from the Field (SMIF)Page 4 sur 4https://surveyinsights.org/?p=13732&preview_id=137322. Groves, R. M., & Heeringa, S. G. (2006). Responsive design for household surveys: tools foractively controlling survey errors and costs. Journal of the Royal Statistical Society: Series A(Statistics in Society), 169(3), 439-457.3. Groves, R. M., & Lyberg, L. (2010). Total survey error: Past, present, and future. Publicopinion quarterly, 74(5), 849-879.4. Koch, A., Blom, A., Stoop, I., & Kappelhof, J. W. (2009). Data collection quality assurance incross-national surveys: The example of the ESS. Methoden, Daten, Analysen (MDA), 3(2),219-247.5. Kreuter, F. (2013). Improving surveys with paradata: Analytic uses of process information.New York: Wiley.6. Lyberg, L. & P. B. Biemer (2008). Quality assurance and quality control in surveys. In E. D.de Leeuw, J. J. Hox, and D. A. Dillman (Eds.): International Handbook of SurveyMethodology (pp. 421-441). New York: Psychology Press7. Lynn, P. (2003). Developing quality standards for cross-national survey research: fiveapproaches. Int. J. Social Research Methodology, 6(4), 323-336.8. Malter, F. (2014). Fieldwork monitoring in the survey of health, ageing and retirement inEurope (SHARE). Survey Methods: Insights from the Field, 8.9. Schouten, B., Bethlehem, J., Beullens, K., Kleven, Ø., Loosveldt, G., Luiten, A., & Skinner, C.(2012). Evaluating, comparing, monitoring, and improving representativeness of surveyresponse through R‐indicators and partial R‐indicators. International Statistical Review,80(3), 382-399.10. Schouten, B., Peytchev, A., & Wagner, J. (2018). Adaptive Survey Design. Boca Raton, FL:CRC Press.11. Schouten, B., Shlomo, N., & Skinner, C. (2011). Indicators for Monitoring and ImprovingRepresentativeness of Response. Journal of Official Statistics 27(2):231–53.12. Wagner, J. (2008). Adaptive Survey Design to Reduce Nonresponse Bias. (PhD thesis),University of Michigan, Ann Arbor, MI.

Fieldwork Monitoring Strategies for Interviewer-Administered Surveys

Meitinger, K.M.

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Fieldwork Monitoring Strategies for Interviewer-Administered Surveys

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