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 - Funke, F. (19)
- Higher Item Nonresponse Rates Caused by Slider Scales in Web Surveys; 2015; Toepoel, V.; Funke, F.
- Investigating Response Quality in Mobile and Desktop Surveys: A Comparison of Radio Buttons, Visual...; 2014; Toepoel, V.; Funke, F.
- The Use of Paradata to Predict Future Cooperation in a Panel Study; 2014; Funke, F., Goeritz, A.
- HTML5 and mobile Web surveys: A Web experiment on new input types; 2013; Funke, F.
- Break-off and attrition in the GIP amongst technologically experienced and inexperienced participants...; 2013; Blom, A. G., Bossert, D., Clark, V., Funke, F., Gebhard, F., Holthausen, A., Krieger, U., Wachenfeld...
- Nonresponse and Nonresponse Bias in a Probability-Based Internet Panel; 2013; Blom, A. G., Bossert, D., Funke, F., Gebhard, F., Holthausen, A., Krieger, U.
- Enhancing Web Surveys With New HTML5 Input Types; 2012; Funke, F.
- Mobile Survey Participation Rates in Commercial Market Research: A Meta-Analysis; 2012; Bosnjak, M., Poggio, T., Becker, K. R., Funke, F., Wachenfeld, A., Fischer, B.
- High potential for mobile Web surveys: Findings from a survey representative for German Internet users...; 2012; Funke, F., Wachenfeld, A.
- Why semantic differentials in Web-based research should be made from visual analogue scales and not...; 2012; Funke, F., Reips, U.-D.
- Web-based rating scales: HTML 5 and other innovations; 2011; Funke, F.
- Ignoring the compatibility of online questionnaires may bias the psychological composition of your sample...; 2011; Funke, F.
- Explaining more variance with visual analogue scales: A Web experiment; 2011; Funke, F.
- Internet-Based Measurement With Visual Analogue Scales: An Experimental Investigation; 2010; Funke, F.
- Making small effects observable: Reducing error by using visual analogue scales; 2009; Funke, F., Reips, U.-D.
- Yes, VASs can! Increasing the accuracy of survey measurements with computerized visual analogue scales...; 2009; Funke, F., Reips, U.-D.
- Response Formats in Cross-cultural Comparisons in Web-based Surveys; 2009; Thomas, R. K.l, Terhanian, G., Funke, F.
- Using Audio and Video Clips in Web Surveys — Feasibility and Impact on Data Quality; 2007; Fuchs, M., Funke, F.
- Dynamic Forms: Online Surveys 2.0 ; 2007; Funke, F., Reips, U.-D.