1. bookVolume 35 (2019): Issue 1 (March 2019)
Journal Details
First Published
01 Oct 2013
Publication timeframe
4 times per year
access type Open Access

The Effect of Survey Mode on Data Quality: Disentangling Nonresponse and Measurement Error Bias

Published Online: 26 Mar 2019
Volume & Issue: Volume 35 (2019) - Issue 1 (March 2019)
Page range: 93 - 115
Received: 01 Apr 2016
Accepted: 01 May 2018
Journal Details
First Published
01 Oct 2013
Publication timeframe
4 times per year

More and more surveys are conducted online. While web surveys are generally cheaper and tend to have lower measurement error in comparison to other survey modes, especially for sensitive questions, potential advantages might be offset by larger nonresponse bias. This article compares the data quality in a web survey administration to another common mode of survey administration, the telephone.

The unique feature of this study is the availability of administrative records for all sampled individuals in combination with a random assignment of survey mode. This specific design allows us to investigate and compare potential bias in survey statistics due to 1) nonresponse error, 2) measurement error, and 3) combined bias of these two error sources and hence, an overall assessment of data quality for two common modes of survey administration, telephone and web.

Our results show that overall mean estimates on the web are more biased compared to the telephone mode. Nonresponse and measurement bias tend to reinforce each other in both modes, with nonresponse bias being somewhat more pronounced in the web mode. While measurement error bias tends to be smaller in the web survey implementation, interestingly, our results also show that the web does not consistently outperform the telephone mode for sensitive questions.


AAPOR, The American Association for Public Opinion Research. 2011. Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys. 7th edition.Search in Google Scholar

Abraham, K.G., A. Maitland, and S.M. Bianchi. 2006. “Nonresponse in the American Time Use Survey. Who is Missing from the Data and How Much Does it Matter?” Public Opinion Quarterly 70: 676–703. Doi: http://dx.doi.org/10.1093/poq/nfl037.10.1093/poq/nfl037Open DOISearch in Google Scholar

Atkeson, L.R., A.N. Adams, and M.R. Alvarez. 2014. “Nonresponse and Mode Effects in Self- and Interviewer-Administered Surveys.” Political Analysis 22: 304–320. Doi: http://dx.doi.org/10.1093/pan/mpt049.10.1093/pan/mpt049Open DOISearch in Google Scholar

Atkeson, L.R., A.N. Adams, L.A. Bryant, L. Zilberman, and K.L. Saunders. 2011. “Considering Mixed Mode Surveys for Questions in Political Behavior: Using the Internet and Mail to Get Quality Data at Reasonable Costs.” Political Behavior 33: 161–178. Doi: http://dx.doi.org/10.1007/s11109-010-9121-1.10.1007/s11109-010-9121-1Open DOISearch in Google Scholar

Bethlehem, J. 2010. “Selection Bias in Web Surveys.” International Statistical Review 78: 161–188. Doi: http://dx.doi.org/10.1111/j.1751-5823.2010.00112.x.10.1111/j.1751-5823.2010.00112.xOpen DOISearch in Google Scholar

Biemer, P.P. 2010. “Overview of Design Issues: Total Survey Error.” In Handbook of Survey Research, edited by P.V. Marsden and J.D. Wright, 27–57. Bingley: Emerald.Search in Google Scholar

Biemer, P.P. and L.E. Lyberg. 2003. Introduction to Survey Quality. New York: Wiley.10.1002/0471458740Search in Google Scholar

Bound, J. and A.B. Krueger. 1991. “The Extent of Measurement Error in Longitudinal Earnings Data: Do Two Wrongs Make a Right?” Journal of Labor Economics 9: 1–24. Doi: http://dx.doi.org/10.3386/w2885.10.3386/w2885Open DOISearch in Google Scholar

Bradburn, N., S. Sudman, and B. Wansink. 2004. Asking Questions. Revised Edition. San Francisco: Jossey-Bass.Search in Google Scholar

Braunsberger, K., H. Wybenga, and R. Gates. 2007. “A Comparison of Reliability Between Telephone and Web-Based Surveys.” Journal of Business Research 60: 758–764. Doi: http://dx.doi.org/10.1016/j.jbusres.2007. DOISearch in Google Scholar

Callegaro, M., R.P. Baker, J. Bethlehem, A.S. Göritz, J.A. Krosnick, and P.J. Lavrakas. 2014. Online Panel Research. A Data Quality Perspective. Chichester: Wiley.10.1002/9781118763520Search in Google Scholar

Chang, L. and J.A. Krosnick. 2009. “National Surveys via RDD Telephone Interviewing Versus the Internet. Comparing Sample Representativeness and Response Quality.” Public Opinion Quarterly 73: 641–678. Doi: http://dx.doi.org/10.1093/poq/nfp075.10.1093/poq/nfp075Open DOISearch in Google Scholar

Chang, L. and J.A. Krosnick. 2010. “Comparing Oral Interviewing With Self-Administered Computerized Questions: An Experiment.” Public Opinion Quarterly 74: 154–167. Doi: http://dx.doi.org/10.1093/poq/nfp090.10.1093/poq/nfp090Open DOISearch in Google Scholar

De Leeuw, E.D. 2005. “To Mix or Not to Mix Data Collection Modes in Surveys.” Journal of Official Statistics 21: 233–255.Search in Google Scholar

De Leeuw, E.D., D.A. Dillman, and J.J. Hox. 2008. “Mixed-Mode Surveys: When and Why.” In International Handbook of Survey Methodology, edited by E.D. de Leeuw, J.J. Hox, and D.A. Dillman, 299–316. New York: Erlbaum/Taylor & Francis.Search in Google Scholar

De Rada, V.D. and S.P. del Amo. 2014. “Two Are Better Than One: The Use of a Mixed-Mode Data Collection to Improve the Electoral Forecast.” Survey Practice 7: 1–6. Doi: http://dx.doi.org/10.29115/SP-2014-0003.10.29115/SP-2014-0003Search in Google Scholar

Dillman, D.A., J.L. Eltinge, R.M. Groves, and R.J.A. Little. 2002. “Survey Nonresponse in Design, Data Collection and Analysis.” In Survey Nonresponse, edited by R.M. Groves, D.A. Dillman, J.L. Eltinge, and R.J.A. Little, 3–26. New York: Wiley.Search in Google Scholar

Dillman, D.A., G. Phelps, R. Tortora, K. Swift, J. Kohrell, J. Berck, and B.L. Messer. 2009. “Response Rate and Measurement Differences in Mixed-Mode Surveys Using Mail, Telephone, Interactive Voice Response (IVR) and the Internet.” Social Science Research 38: 1–18. Doi: http://dx.doi.org/10.1016/j.ssresearch.2008. DOISearch in Google Scholar

Duffy, B., K. Smith, G. Terhanian, and J. Bremer. 2005. “Comparing Data from Online and Face-to-Face Surveys.” International Journal of Market Research 47: 615–639. Doi: http://doi.org/10.1177/147078530504700602.10.1177/147078530504700602Open DOISearch in Google Scholar

Duncan, G. and D. Hill. 1985. “An Investigation of the Extent and Consequences of Measurement Error in Labor-Economic Survey Data.” Journal of Labor Economics 3: 508–532. Doi: http://dx.doi.org/10.1086/298067.10.1086/298067Open DOISearch in Google Scholar

Eckman, S., F. Kreuter, A. Kirchner, A. Jäckle, S. Presser, and R. Tourangeau. 2014. “Assessing the Mechanisms of Misreporting to Filter Questions in Surveys.” Public Opinion Quarterly 78: 721–733. Doi: http://dx.doi.org/10.1093/poq/nfu030.10.1093/poq/nfu030Open DOISearch in Google Scholar

Fricker, S., M. Galesic, R. Tourangeau, and T. Yan. 2005. “An Experimental Comparison of Web and Telephone Surveys.” Public Opinion Quarterly 6: 370–392. Doi: http://dx.doi.org/10.1093/poq/nfi027.10.1093/poq/nfi027Open DOISearch in Google Scholar

Groves, R.M. 2004. Survey Error and Survey Costs. Hoboken: Wiley & Sons.Search in Google Scholar

Groves, R.M. 2006. “Nonresponse Rates and Nonresponse Bias in Household Surveys.” Public Opinion Quarterly 70: 646–675. Doi: http://dx.doi.org/10.1093/poq/nfl033.10.1093/poq/nfl033Open DOISearch in Google Scholar

Groves, R.M. and M. Couper. 1998. Nonresponse in Household Interview Surveys. Wiley Series in Probability and Statistics: Survey Methodology Section. New York: Wiley.10.1002/9781118490082Search in Google Scholar

Hope, S., P. Campanelli, G. Nicolaas, P. Lynn, and A. Jäckle. 2014. “The Role of the Interviewer in Producing Mode Effects: Results from a Mixed Modes Experiment Comparing Face-to-Face, Telephone and Web Administration.” ISER Working Paper Series No. 2014-20: 1–41. Available at: http://hdl.handle.net/10419/123808 (accessed December 2014).Search in Google Scholar

IAB (Institut für Arbeitsmarkt- und Berufsforschung). 2011. Nuremberg: Integrierte Erwerbsbiographien (IEB) V09.00.Search in Google Scholar

IAB (Institut für Arbeitsmarkt- und Berufsforschung). 2012. Nuremberg: Leistungshistorik Grundsicherung (LHG), Version 06.06.Search in Google Scholar

IAB (Institut für Arbeitsmarkt- und Berufsforschung). 2013. Nuremberg: Beschäftigtenhistorik (BeH), Version 09.03.00.Search in Google Scholar

Jacobebbinghaus, P. and S. Seth. 2007. “The German Integrated Employment Biographies Sample IEBS.” Schmollers Jahrbuch 127: 335–342.Search in Google Scholar

Kreuter, F. and K. Olson. 2011. “Multiple Auxiliary Variables in Nonresponse Adjustment.” Sociological Methods & Research 40: 311–332. Doi: http://dx.doi.org/10.1177/0049124111400042.10.1177/0049124111400042Open DOISearch in Google Scholar

Kreuter, F., K. Olson, J. Wagner, T. Yan, T. Ezatti-Rice, C. Casas-Cordero, A. Petychev, R. M. Groves, and T. Raghuatan. 2010. “Using Proxy Measures and Other Correlates of Survey Outcomes to Adjust for Non-Response: Examples from Multiple Surveys.” Journal of the Royal Statistical Society: Series A (Statistics in Society) 173: 389–407. Doi: http://dx.doi.org/10.1111/j.1467-985X.2009.00621.x.10.1111/j.1467-985X.2009.00621.xOpen DOISearch in Google Scholar

Kreuter, F., S. Presser, and R. Tourangeau. 2008. “Social Desirability Bias in CATI, IVR, and Web Surveys. The Effects of Mode and Question Sensitivity.” Public Opinion Quarterly 72: 847–865. Doi: http://dx.doi.org/10.1093/poq/nfn063.10.1093/poq/nfn063Open DOISearch in Google Scholar

Lee, R.M. 1993. Doing Research on Sensitive Topics. London: Sage.Search in Google Scholar

Letourneau, P.M. and A.A. Zbikowski. 2008. “Nonresponse in the American Time Use Survey.” In Proceedings of the Section on Survey Research Methods: American Statistical Association, August 4, 2008. 1283–1290. Denver, CO: American Statistical Association. Available at: http://ww2.amstat.org/sections/srms/Proceedings/y2008/Files/300982.pdf (accessed April 2018).Search in Google Scholar

Lozar Manfreda, K., M. Bosnjak, J. Berzelak, I. Haas, and V. Vehovar. 2008. “Web Surveys Versus Other Survey Modes. A Meta-Analysis Comparing Response Rates.” International Journal of Market Research 50: 79–104. Doi: http://dx.doi.org/10.1177/147078530805000107.10.1177/147078530805000107Open DOISearch in Google Scholar

Malhotra, N., J.M. Miller, and J. Wedeking. 2014. “The Relationship Between Nonresponse Strategies and Measurement Error. Comparing Online Panels to Traditional Surveys.” In Online Panel Research. A Data Quality Perspective, edited by M. Callegaro, R. Baker, J. Bethlehem, A.S. Göritz, J. Krosnick, and P.J. Lavrakas, 313–336. Chichester: Wiley.10.1002/9781118763520.ch14Search in Google Scholar

McCabe, S.E., C.J. Boyd, M.P. Couper, S. Crawford, and H. D’Arcy. 2002. “Mode Effects for Collecting Alcohol and Other Drug Use Data: Web and U.S. Mail.” Journal of Studies on Alcohol 63: 755–761. Doi: http://dx.doi.org/10.15288/jsa.2002.63.755.10.15288/jsa.2002.63.75512529076Search in Google Scholar

Olson, K. 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 (Statistics in Society) 176: 129–145. Doi: http://dx.doi.org/10.1111/j.1467-985X.2012.01042.x.10.1111/j.1467-985X.2012.01042.xOpen DOISearch in Google Scholar

O’Neill, G. and J. Dixon. 2005. “Nonresponse Bias in the American Time Use Survey.” In Proceedings of the Section on Survey Research Methods: American Statistical Association, August 10, 2005. 2958–2966. Minneapolis, MN: American Statistical Association. Available at: http://ww2.amstat.org/sections/srms/Proceedings/y2005/Files/JSM2005-000193.pdf (accessed April 2018).Search in Google Scholar

Roberts, C., N. Allum, and P. Sturgis. 2014. “Nonresponse and Measurement Error in an Online Panel. Does Additional Effort to Recruit Reluctant Respondents Result in Poorer Data Quality?” In Online Panel Research. A Data Quality Perspective, edited by M. Callegaro, R. Baker, J. Bethlehem, A.S. Göritz, J. Krosnick, and P.J. Lavrakas, 337–362. Chichester: Wiley.10.1002/9781118763520.ch15Search in Google Scholar

Rodgers, W.L., C. Brown, and G.J. Duncan. 1993. “Errors in Survey Reports of Earnings, Hours Worked, and Hourly Wages.” Journal of the American Statistical Association 88: 1208–1218. Doi: http://dx.doi.org/10.1080/01621459.1993.10476400.10.1080/01621459.1993.10476400Open DOISearch in Google Scholar

Sakshaug, J.W. and F. Kreuter. 2012. “Assessing the Magnitude of Non-Consent Biases in Linked Survey and Administrative Data.” Survey Research Methods 6: 113–122. Doi: http://dx.doi.org/10.18148/srm/2012.v6i2.5094.Search in Google Scholar

Sakshaug, J.W., T. Yan, and R. Tourangeau. 2010. “Nonresponse Error, Measurement Error, and Mode of Data Collection: Tradeoffs in a Multi-Mode Survey of Sensitive and Non-Sensitive Items.” Public Opinion Quarterly 74: 907–933. Doi: http://dx.doi.org/10.1093/poq/nfq057.10.1093/poq/nfq057Open DOISearch in Google Scholar

Sanders, D., H.D. Clarke, M.C. Stewart, and P. Whiteley. 2007. “Does Mode Matter for Modelling Political Choice? Evidence from the 2005 British Election Study.” Political Analysis 15: 257–285. Doi: http://dx.doi.org/10.1093/pan/mpl010.10.1093/pan/mpl010Open DOISearch in Google Scholar

Sax, L.J., S.K. Gilmartin, and A.N. Bryant. 2003. “Assessing Response Rates and Nonresponse Bias in Web and Paper Surveys.” Research in Higher Education 44: 409–432. Doi: http://dx.doi.org/10.1023/A:1024232915870.10.1023/A:1024232915870Open DOISearch in Google Scholar

Schouten, B., F. Cobben, P. Lundquist, and J. Wagner. 2016. “Does More Balanced Survey Response Imply Less Non-Response Bias?” Journal of the Royal Statistical Society: Series A (Statistics in Society) 179: 727–748. Doi: http://dx.doi.org/10.1111/rssa.12152.10.1111/rssa.12152Open DOISearch in Google Scholar

Statistisches Bundesamt. 2013. Wirtschaftsrechnungen. Private Haushalte in der Informationsgesellschaft – Nutzung von Informations – und Kommunikationstechnologien. Wiesbaden, Germany: Statistisches Bundesamt.Search in Google Scholar

Stephenson, L.B. and J. Cre^te. 2011. “Studying Political Behavior: A Comparison of Internet and Telephone Surveys.” International Journal of Public Opinion Research 23: 24–55. Doi: http://dx.doi.org/10.1093/ijpor/edq025.10.1093/ijpor/edq025Open DOISearch in Google Scholar

Vannieuwenhuyze, J., G. Loosveldt, and G. Molenberghs. 2010. “A Method for Evaluating Mode Effects in Mixed-Mode Surveys.” Public Opinion Quarterly 74: 1027–1045. Doi: http://dx.doi.org/10.1093/poq/nfq059.10.1093/poq/nfq059Open DOISearch in Google Scholar

Yeager, D.S., J.A. Krosnick, L. Chang, H.S. Javitz, M.S. Levendusky, A. Simpser, and R. Wang. 2011. “Comparing the Accuracy of RDD Telephone Surveys and Internet Surveys Conducted with Probability and Non-Probability Samples.” Public Opinion Quarterly 75: 709–747. Doi: http://dx.doi.org/10.1093/poq/nfr020.10.1093/poq/nfr020Open DOISearch in Google Scholar

Recommended articles from Trend MD

Plan your remote conference with Sciendo