Web Survey Bibliography
Title The Adequacy of Outlier Definitions based on Response Time Distributions in Web Surveys: A Paradata Usability Study
Author Schlosser, S.; Karem Hoehne, J.
Year 2016
Access date 29.04.2016
Presentation PDF (625KB)
Abstract
Relevance and Research Question: Web surveys are commonly used for data collection in empirical social research because they are cheaper, faster, and simpler to conduct than other survey modes. Furthermore, they enable researchers to capture a variety of additional data (so-called paradata) during the survey process such as response times. Measuring response times has by now a long tradition in social psychological research as well as survey research to investigate response behavior and response processes. One key problem, however, is the determination of appropriate thresholds to define outliers; to a certain degree researchers determine them arbitrarily. Until now, there is no scientific consensus with respect to the definition of outliers.
Methods and Data: In our study we developed an (innovative) two-stage outlier definition procedure for web surveys using paradata. This approach is based on the activity of the web survey while processing, accompanied by an outlier definition that is based on the distribution of the response times. Our web survey (n = 1899) is based on an onomastic sampling approach and contained individual questions as well as grid questions. Moreover, we tested different procedures for dealing with outliers based on the response time distributions.
Results: Our analyses show that common outlier definition procedures, which are based on the distributions of response times, provide insufficient results. This implies that they are frequently unable to capture respondents who leave the web survey for a short time period so that the response times are biased upwards. Particularly, this circumstance can be observed for grid questions.
Added Value: Altogether, our findings suggest that the two-stage outlier definition procedure is superior to common methods for dealing with outliers that are only based on response time distributions.
Methods and Data: In our study we developed an (innovative) two-stage outlier definition procedure for web surveys using paradata. This approach is based on the activity of the web survey while processing, accompanied by an outlier definition that is based on the distribution of the response times. Our web survey (n = 1899) is based on an onomastic sampling approach and contained individual questions as well as grid questions. Moreover, we tested different procedures for dealing with outliers based on the response time distributions.
Results: Our analyses show that common outlier definition procedures, which are based on the distributions of response times, provide insufficient results. This implies that they are frequently unable to capture respondents who leave the web survey for a short time period so that the response times are biased upwards. Particularly, this circumstance can be observed for grid questions.
Added Value: Altogether, our findings suggest that the two-stage outlier definition procedure is superior to common methods for dealing with outliers that are only based on response time distributions.
Access/Direct link Conference Homepage (presentation)
Year of publication2016
Bibliographic typeConferences, workshops, tutorials, presentations
Web survey bibliography - Germany (361)
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- 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.
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- 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.
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- What Does the Satisfaction with Democracy Measure Mean to Respondents in Different Countries? How Cross...; 2014; Behr, D., Braun, M.
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- 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.