Web Survey Bibliography
Relevance & Research Question: Surveys sometimes include sensitive topics, e.g. sexual behavior or tax evasion. Respondents often hesitate to answer such sensitive items which results in high item non-response rates and a specific type of response error: a tendency to underreport socially undesirable and overreport desirable behavior. The randomized response technique (RRT) (Warner, 1965) is a well-known survey technique to reduce the problem of misreporting by protecting the privacy of the respondents. However, to obtain valid and reliable data, respondents have to understand and follow the technique´s instructions. Cheating detection models (e.g. Clark & Desharnais, 1998) try to identify the respondents which do not act according to the instructions of the design (and, hence, are cheating). Web surveys offer the opportunity to “observe” the respondents´ answering process by means of additional so-called paradata. In this study we present a new approach to detect cheaters using such client-side paradata (especially item response times).
Methods & Data: We conducted a web survey during the university´s open house (N=159) using the RRT to estimate the prevalence of deceiving in a partnership. To assess the individual item response times we implemented two comparable experimental situations; the classical RRT (including a sensitive question) and a similar RR design (without a sensitive question). Assuming that cheaters give quick answers without paying much attention to the content of the question we finally tested whether the individual item response times are significantly different in both settings.
Results: We found a small proportion of cheaters. The detected proportion of cheaters has an effect on the estimated proportion of people carrying the sensitive characteristic as a comparison with the unadjusted estimator shows.
Added Value: Previous research on cheating detection has focused only on the aggregated quantity and not on the individual “quality” of cheaters. The data quality of answers to sensitive questions is improved with such a cheating detection method based on an individual level. Here item response times (and other client-side paradata) could prospectively contribute to improve the estimation process.
Web survey bibliography - Germany (361)
- Does the Use of Mobile Devices (Tablets and Smartphones) Affect Survey Quality and Choice Behaviour...; 2015; Glenk, K.; Liebe, U.; Oehlmann, M.
- Does Personalized Feedback Increase Respondent Motivation?; 2015; Kroh, M.; Kuhne, S.
- Direction of Response Format in Web and Paper & Pencil Surveys; 2015
- Nonresponse and Measurement Bias in Web surveys ; 2015; Metzler, A.; Fuchs, M.
- Deep impact or no impact, evaluating opportunities for a new question type: Statement allocation on...; 2015; Schmidt, S.
- Approaches for Evaluating Online Survey Response Quality; 2015; Gluck, N.
- Positioning of Clarification Features in Open Frequency and Open Narrative Questions; 2015; Fuchs, M.; Metzler, A.
- A Systematic Generation of an Email Pool for Web Surveys; 2015; Silber, H.; Leibold, J.; Lischewski, J.; Schlosser, S.
- 640 Current trends in management of high-risk prostate cancer in Europe: Results of a web-based survey...; 2014; Briganti, A., Isbarn, H., Ost, P., Ploussard, G., Sooriakumaran, P., Van Den Bergh, R.C.N., Van Oort...
- Disclosure of sensitive behaviors across self-administered survey modes: a meta-analysis; 2014; Gnambs, T., Kaspar, K.
- Open-ended questions in Web Surveys-Using visual and adaptive questionnaire design to improve narrative...; 2014; Emde, M.
- Query on Data Collection for Social Surveys; 2014; Blanke, K., Luiten, A.
- Why Do Respondents Break Off Web Surveys and Does It Matter? Results From Four Follow-up Surveys; 2014; Rossmann, J., Blumenstiel, J. E., Steinbrecher, M.
- The Effectiveness of Mailed Invitations for Web Surveys and the Representativeness of Mixed-Mode versus...; 2014; Bandilla, W., Couper, M. P., Kaczmirek, L.
- Post-endodontic treatment of incisors and premolars among dental practitioners in Saarland: an interactive...; 2014; Mitov, G., Doerr, M., Nothdurft, F. P., Draenert, F., Pospiech, P. R.
- Mixed-Mode Designs bei Erhebungen mit sensitiven Fragen: Einfluss auf das Teilnahme- und Antwortverhalten...; 2014; Krug, G., Kriwy, P., Carstensen, J.
- Mining “Big Data” using Big Data Services ; 2014; Reips, U.-D., Matzat, U.
- Instant Interactive Feedback in Grid Questions: Reminding Web Survey; 2014; Kunz, T., Fuchs, M.
- What Does the Satisfaction with Democracy Measure Mean to Respondents in Different Countries? How Cross...; 2014; Behr, D., Braun, M.
- Determinants of the starting rate and the completion rate in online panel studies; 2014; Goeritz, A.
- Assessing representativeness of a probability-based online panel in Germany; 2014; Struminskaya, B., Kaczmirek, L., Schaurer, I., Bandilla, W.
- The Influence of the Answer Box Size on Item Nonresponse to Open-Ended Questions in a Web Survey; 2014; Zuell, C., Menold, N., Koerber, S.
- Does the Choice of Header Images influence Responses? Findings from a Web Survey on Students’...; 2014; Barth, A.
- Using Paradata to Predict and to Correct for Panel Attrition in a Web-based Panel Survey; 2014; Rossmann, J., Gummer, T.
- Offline Households in the German Internet Panel; 2014; Bossert, D., Holthausen, A., Krieger, U.
- Which fieldwork method for what target group? How to improve response rate and data quality; 2014; Wulfert, T., Woppmann, A.
- Switching the polarity of answer options within the questionnaire and using various numbering schemes...; 2014; Struminskaya, B., Schaurer, I., Bosnjak, M.
- Improving cheater detection in web-based randomized response using client-side paradata; 2014; Dombrowski, K., Becker, C.
- Interest Bias – An Extreme Form of Self-Selection?; 2014; Cape, P. J., Reichert, K.
- Increasing data quality in online surveys 4.1; 2014; Hoeckel, H.
- Moving answers with the GyroScale: Using the mobile device’s gyroscope for market research purposes...; 2014; Luetters, H., Kraus, M., Westphal, D.
- Confirmation Bias in Web-Based Search: A Randomized Online Study on the Effects of Expert Information...; 2014; Schweiger, S., Oeberst, A., Cress, U.
- Undisclosed Privacy: The Effect of Privacy Rights Design on Response Rates; 2014; Haer, R., Meidert, N.
- The Effect of Benefit Wording on Consent to Link Survey and Administrative Records in a Web Survey; 2014; Sakshaug, J. W., Kreuter, F.
- GESIS Panel: Sample and Recruitment; 2014
- The Use of Paradata to Predict Future Cooperation in a Panel Study; 2014; Funke, F., Goeritz, A.
- Incentives on demand in a probability-based online panel: redemption and the choice between pay-out...; 2014; Schaurer, I., Struminskaya, B., Kaczmirek, L.
- Responsive designed web surveys; 2014; Dreyer, M., Reich, M., Schwarzkopf, K.
- Extra incentives for extra efforts – impact of incentives for burdensome tasks within an incentivized...; 2014; Schreier, J. H., Biethahn, N., Drewes, F.
- Innovation for television research - online surveys via HbbTV. A new technology with fantastic opportunities...; 2014; Herche, J., Adler, M.
- Asking Sensitive Questions: An Evaluation of the Randomized Response Technique Versus Direct Questioning...; 2013; Wolter, F.; Preisendoerfer, P.
- Respondent Choice of Survey Mode; 2013; Fuchs, M.
- Development and validation of a single- item scale for the relative assessment of physical attractiveness...; 2013; Lutz, J.; Kemper, C. J.; Beierlein, C.; etc.
- Accounting for the Effects of Data Collection Method Application to the International Tobacco Control...; 2013; Thompson, M. E.; Huang, Y. C.; Boudreau, C.; Fong, G. T.; van den Putte, B.; Nagelhout, G. E.; Willemsen...
- The Short-term Campaign Panel of the German Longitudinal Election Study 2009. Design, Implementation...; 2013; Steinbrecher, M., Rossmann, J.
- Too Fast, Too Straight, Too Weird: Post Hoc Identification of Meaningless Data in Internet ; 2013; Leiner, D. J.
- The Digital Divide in Europe; 2013; Zillien, N.; Marr, M.
- The Recruitment of the Access Panel of German Official Statistics from a Large Survey in 2006: Empirical...; 2013; Amarov, B.; Rendtel, U.
- Online, face-to-face and telephone surveys—Comparing different sampling methods in wine consumer...; 2013; Szolnoki, G., Hoffmann, D.
- Where does the Fair Trade price premium go? Confronting consumers' request with reality; 2013; Langen, N., Adenaeuer, L.