Web Survey Bibliography
(a) Relevance & Research Question
Online surveys are fast, efficient, and especially cheap. Self-administered surveys might even produce higher data quality compared to personal or phone interviews, e.g. for lower social desirability bias. However, web surveys also face specific problems such as the absence of a human interviewer. Among other things, this limits interview supervision, possibly causing higher item nonresponse and increasing satisficing behavior.
Generally, survey results largely differ depending on collection mode. For instance, recency effects are more likely in oral interviews, which also tend to produce more extreme answers and acquiescence bias, while primacy effects are associated with visual questionnaire presentation. Furthermore, mixed-mode surveys have received growing attention. Since mode effects are of particular relevance there, we will also cover this aspect.
Against this background, analyzing mode effects between traditional modes and web surveys, we show to what extent the latter can be a suitable alternative.
(b) Methods & Data
In the first step, data from three different GLES components are compared, including face-to-face, CATI, and online surveys.
In the second step, we use data from GLES long-term panel. As the second panel wave was collected in a mixed-mode design combining CATI with mail interviews, we compare changes for the sub-samples relative to the first (face-to-face) panel wave.
In terms of methods, we primarily rely on univariate statistics (frequencies, distributions, mean values, variance). We focus on well-established items measuring electoral choice, political attitudes, and psychological predispositions. Beyond, we estimate multivariate models, including interaction terms with survey mode.
(c) Results
Preliminary results uncover a number of clear mode effects between personal, phone, and web surveys. These differences are anything but uniform, though. Rather, we observe differences for specific variables and under specific conditions only.
(d) Added Value
Never before in German electoral science has a similarly coherent questionnaire been implemented in three different survey modes during the same field period. GLES data therefore allow for detailed and unprecedented analyses of mode effects, including mixed-mode surveys. Our results add to the understanding of differences between personal, phone, and web surveys, and suggest what can be done to prevent those differences.
Conference Homepage (abstract) / (full text)
Web Survey Bibliography - Nonresponse (1931)
- Using Multiple Modes in Follow-Up Contacts in Random-Digit Dialing Surveys; 2013; Chowdhury, P. P.
- Tablets and Smartphones and Netbooks, Oh My! Effects of Device Type on Respondent Behavior; 2013; Ross, H., Mendelson, J., Lackey, M.
- Impacts of Unit Nonresponse in a Recontact Study of Youth; 2013; Mendelson, J., Viera Jr., L.
- Multi-Mode Survey Administration: Does Offering Multiple Modes at Once Depress Response Rates?; 2013; Newsome, J., Levin, K., Langetieg, P., Vigil, M., Sebastiani, M.
- Responsive Design for Web Panel Data Collection; 2013; Bianchi, A., Biffignandi, S.
- Utilizing the Web in a Multi-Mode Survey; 2013; Venkataraman, L.
- Changing to a Mixed-Mode Design: The Role of Mode in Respondents’ Decisions About Participation...; 2013; Collins, D., Mitchell, M., Toomes, M.
- Comparing the Effects of Mode Design on Response Rate, Representativeness, and Cost Per Complete in...; 2013; Tully, R.
- Internet Response for the Decennial Census – 2012 National Census Test; 2013; Reiser, C.
- The Effects of Pushing Web in a Mixed-Mode Establishment Data Collection; 2013; Ellis, C.
- Effects of Lotteries on Response Behavior in Online Panels; 2013; Goeritz, A., Luthe, S. C.
- Lotteries and study results in market research online panels; 2013; Goeritz, A., Luthe, S. C.
- Using Paradata to Study Response to Within-Survey Requests; 2013; Sakshaug, J. W.
- Improving Surveys with Paradata: Analytic Uses of Process Information; 2013; Kreuter, F.
- A nationwide web-based freight data collection; 2013; Samimi, A., Mohammadian, A., Kawamura, K.
- Mode Matters: Evaluating Response Comparability in a Mixed-Mode Survey; 2013; Bowyer, B. T., Rogowski, J. C.
- Comparing Survey Results Obtained via Mobile Devices and Computers: An Experiment With a Mobile Web...; 2013; de Bruijne, M., Wijnant, A.
- Methodological Considerations of Qualitative Email Interviews; 2013; Nehls, K.
- Reducing Response Burden for Enterprises Combining Methods for Data Collection on the Internet; 2013; Vik, T.
- Advancing Research Methods with New Technologies; 2013; Sappleton, N.
- Data Quality in PC and Mobile Web Surveys; 2013; Mavletova, A. M.
- By the Numbers: Theory of adaptation or survival of the fittest?; 2013; Cavallaro, K.
- Designing and conducting business surveys; 2013; Snijkers, G.,Araldsen, G., , Willimack, D. K.Jones, J.
- Do I Have Your Full Attention?; 2013; Cape, P. J.
- Optimizing Surveys for Smartphones: Maximizing Response Rates While Minimizing Bias; 2013; Lattery, K., Park Bartolone, G., Saunders, T.
- Solving the Unintentional Mobile Challenge; 2013; Peterson, G., Mechling, J., LaFrance, J., Ham, G.
- Mobile Research Risk: What Happens to Data Quality When Respondents Use a Mobile Device for a Survey...; 2013; Baker-Prewitt, J.
- Challenges for Researchers Investigating Contraceptive Use and Pregnancy Intentions of Young Women Living...; 2013; Herbert, D. L., Loxton, D., Bateson, D., Weisberg, E., Lucke, J. C.
- Using a web-based survey tool to undertake a Delphi study: Application for nurse education research; 2013; Gill, F. J., Leslie, G. D., Grech, C., Latour, J. M.
- Addressing Survey Nonresponse Issues: Implications for ATE Principal Investigators, Evaluators, and...; 2013; Welch, W. W., Barlau, A. N.
- Pros and cons of virtual interviewers – vote in the discussion about surveytainment; 2013; Póltorak, M., Kowalski, J.
- Examination of the equivalence of self-report survey-based paper-and-pencil and internet data collection...; 2013; Weigold, A., Weigold, I. K., Russell, E. J.
- An Assessment of Incentive Versus Survey Length Trade-offs in a Web Survey of Radiologists; 2013; Ziegenfuss, J. Y., Niederhauser, B. D., Kallmes, D., Beebe, T. J.
- Using Online and Paper Surveys - The Effectiveness of Mixed-Mode Methodology for Populations Over 50; 2013; De Bernardo, D. H., Curtis, A.
- The monetary value of good questionnaire design; 2013; Tress, F.
- Slide to ruin data: How slider scales may negatively affect data quality and what to do about it; 2013; Funke, F.
- Measuring wages via a volunteer web survey – a cross-national analysis of item nonresponse; 2013; Steinmetz, S., Annmaria, B.
- Does one really know?: Avoiding noninformative answers in a reliable way.; 2013; de Leeuw, E. D., Boevee, A., Hox, J.
- Sensitive Topics in PC and Mobile Web Surveys; 2013; Mavletova, A. M., Couper, M. P.
- Mobile Research Performance: How Mobile Respondents Differ from PC Users Concerning Interview Quality...; 2013; Schmidt, S., Wenzel, O.
- Who responds to website visitor satisfaction surveys?; 2013; Andreadis, I.
- Why are you leaving me?? - Personality predictors of answering drop out in an online-study; 2013; Thielsch, M., Nestler, S., Back, M.
- Seducing the respondent – how to optimise invitations in on-site online research?; 2013; Póltorak, M., Kowalski, J.
- E-questionnaire in cross-sectional household surveys; 2013; Karaganis, M.
- GESIS Online Panel Pilot: Results from a Probability-Based Online Access Panel; 2013; Kaczmirek, L., Bandilla, W., Schaurer, I., Struminskaya, B., Weyandt, K.
- How the screen-out influence the dropout of a commercial panel; 2013; Bartoli, B.
- 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.
- Rewards - Money for Nothing?; 2013; Cape, P. J., Martin, P.
- Effects of incentive reduction after a series of higher incentive waves in a probability-based online...; 2013; Struminskaya, B., Kaczmirek, L., Schaurer, I., Bandilla, W.
