Web Survey Bibliography
Relevance & Research Question: In panel studies, low attrition is especially important, because only complete data sets across waves can be analyzed. Survey paradata (e.g., response times, item nonresponse, or break-off) can be collected at moderate cost. In this explorative study, we analyze if paradata lend themselves to predict non-participation in future waves.
Methods & Data: Members of a commercial online panel were invited to participate in an academic study on the stability of personal preferences and traits. The questionnaire consisted of questions regarding biometrics (e.g., size, eye color, handedness), preference for certain pictures, preference for certain foods, and items to measure personality traits. Invitations to identical questionnaires were sent in December 2011, June 2012, December 2012, and June 2013.
Results: Overall, 807 respondents participated in Wave 1 and 249 respondents in all four waves. The completion rate continuously rose from 91.8% (Wave 1) to 98.4% (Wave 4). Break-off in one wave proved to be a good indicator for refusal to participate in the next wave: The chances that a participant completed wave n were more than 3.5 times higher for those who completed wave n-1 than for those who did not complete wave n-1. Reminder emails were most effective in the first wave. Neither item nonresponse nor response times were good indicators to predict future participation.
Added Value: In longitudinal studies there is a high risk of loosing respondents. Break-off in one wave proved to be a predictor for break-off in subsequent waves. We discuss how paradata can be taken advantage of to lower panel attrition.
GOR Homepage (abstract) / (presentation)
Web survey bibliography - General Online Research Conference (GOR) 2014 (29)
- Using Paradata to Predict and to Correct for Panel Attrition in a Web-based Panel Survey; 2014; Rossmann, J., Gummer, T.
- Targeting the bias – the impact of mass media attention on sample composition and representativeness...; 2014; Steinmetz, S., Oez, F., Tijdens, K. G.
- 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.
- Exploring selection biases for developing countries - is the web a promising tool for data collection...; 2014; Tijdens, K. G., Steinmetz, S.
- Evaluating mixed-mode redesign strategies against benchmark surveys: the case of the Crime Victimization...; 2014; Klausch, L. T., Hox, J., Schouten, B.
- The quality of ego-centered social network data in web surveys: experiments with a visual elicitation...; 2014; Marcin, B., Matzat, U., Snijders, C.
- Switching the polarity of answer options within the questionnaire and using various numbering schemes...; 2014; Struminskaya, B., Schaurer, I., Bosnjak, M.
- Measuring the very long, fuzzy tail in the occupational distribution in web-surveys; 2014; Tijdens, K. G.
- Social Media and Surveys: Collaboration, Not Competition; 2014; Couper, M. P.
- 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.
- Online Qualitative Research – Personality Matters ; 2014; Tress, F., Doessel, C.
- 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.
- Online Surveys as a Management Tool for Monitoring Multicultual Virtual Team Processes; 2014; Scovotti, C.
- How much is shorter CAWI questionnaire VS CATI questionnaire?; 2014; Bartoli, B.
- WEBDATANET: A Network on Web-based Data Collection, Methodological Challenges, Solutions, and Implementation...; 2014; Tijdens, K. G., Steinmetz, S., de Pedraza, P., Serrano, F.
- 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.
- The Effect of De-Contextualisation - A Comparison of Response Behaviour in Self-Administered Surveys; 2014; Wetzelhuetter, D.
- 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.
- Students First Choice – the influence of mobile mode on results; 2014; Maxl, E.
- Device Effects: How different screen sizes affect answer quality in online questionnaires; 2014; Fischer, B., Bernet, F.
- Moving towards mobile ready web panels; 2014; Wijnant, A., de Bruijne, M.
- Innovation for television research - online surveys via HbbTV. A new technology with fantastic opportunities...; 2014; Herche, J., Adler, M.
- Mixed-devices in a probability based panel survey. Effects on survey measurement error; 2014; Toepoel, V., Lugtig, P. J.
- Online mobile surveys in Italy: coverage and other methodological challenges; 2014; Poggio, T.