Web Survey Bibliography
Relevance & Research Question: Web surveys of the general population are suspected to yield less representative samples than traditional survey modes for two major reasons. First, population coverage with internet access is incomplete in most countries. Second, response rates to Web surveys are generally lower than in traditional modes. Sequential mixed-mode strategies using personal (CAPI) or telephone (CATI) interviews have been suggested to cope with the presumed representativity problem. In this study we assess the underlying assumptions of this reasoning, i.e., first, whether a probability sample using Web for data collection is less representative than other modes and, second, whether CAPI or CATI possess properties that can compensate for bias when added in sequence to Web.
Methods & Data: We conducted an experiment based on a national probability sample of 8,800 persons in the context of the Dutch ‘Security Monitor’ survey. Persons were assigned to one out of four modes (Web, Mail, CATI, CAPI). Mailed invitations contained a link (Web), a questionnaire (Mail), or announced the contact by an interviewer (CAPI/CATI). After 4-8 weeks we approached every person again in a second wave, either by CAPI or CATI. We included questions on internet coverage in this wave. To assess representativity, background data was available from national registries.
Results: Though The Netherlands are a country of high internet coverage, the impact of under-coverage on representativity was strong (assessed by R-indicators). However, many of the coverage deficits were mitigated in the process of contact and cooperation. The final Web response sample was as representative as CAPI and even more representative than CATI and Mail. Mixing modes in sequence (i.e. Web followed by CAPI or CAPI+CATI) was not capable of compensating the deficits of Web beyond well-known net increases in response rates.
Added Value: Our results question two basic assumptions about Web surveys and mixed-mode designs. We suggest that Web surveys possess equally good or better response properties as traditional modes, if they are based on probability samples and population coverage with internet access is high. Also, from a representativity perspective, we did not find evidence in favour of using mixed-mode designs.
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Web Survey Bibliography - Nonresponse (1921)
- 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.
- Timing of Nonparticipation in an Online Panel: The effect of incentive strategies; 2013; Douhou, S., Scherpenzeel, A.
- Mixed-mode including web: Recent developments at Statistics Netherlands; 2013; Luiten, A., Schouten, B.
- Surveys on Mobile Devices: Opportunities and Challenges; 2013; Couper, M. P.
- Experiences from a probability-based Internet panel: Sample, recruitment and participation; 2013; Scherpenzeel, A.
- Participation and engagement in web surveys of the general population: An overview of challenges and...; 2013; Roberts, C.
- Using Web Survey Panels to Estimate Population Characteristics: A Comparison of Alternative Approaches...; 2013; Rivers, D.
- Online Research, Game On!; 2013; Puleston, J.
- The Design of Grids in Web Surveys; 2013; Couper, M. P., Tourangeau, R., Conrad, F. G., Zhang, C.
- Understanding and Applying Research Design; 2013; Abbott, M. L., McKinney, J.
- Virtual Research Methods; 2013; Hine, C.