Web Survey Bibliography
Relevance and research question: Cost pressures continue to necessitate switching single-mode designs, such as face-to-face (F2F), to inexpensive mixed-mode (MM) designs. This, however, involves the risk of finding different estimates in the MM and single-mode designs, if total survey error is affected by the redesign strategy. Differences in measurement and non-observation error are particularly relevant candidates for design differences in total error, also called measurement and selection effects (MEs and SEs). Knowledge about these effects is relevant to evaluate the usefulness of a MM redesign. We demonstrate the estimation of MEs and SEs for the case of the Dutch Crime Victimization Survey (CVS).
Methods and Data: We administered a split-ballot design, in which four independent samples (n=2,200 each) were drawn from the Dutch population register and assigned either to one of three sequential mixed-mode surveys (web, mail, and telephone, followed by F2F, respectively) or to a single-mode F2F condition, which served as benchmark. Additionally, the respondents to web, mail and telephone were approached a second time in F2F after four weeks. This step made available ‘within-subject’ estimates of MEs, which were exploited to disentangle MEs and SEs in the split-ballot design.
Results: Largest design differences in estimates were found for the mixed-mode mail-F2F design and, with smaller magnitude, also for web-F2F. The telephone-F2F survey showed mainly insignificant differences against the benchmark. In evaluating MEs and SEs, we found that MEs were the predominant cause of the differences between both, mail-F2F and web-F2F, and the benchmark, whereas SEs were generally very small. MEs and SEs were absent when comparing telephone-F2F against F2F.
Added Value: In the CVS case, the large MEs for the mail-F2F and web-F2F designs would require further redesign of questionnaires (e.g. by unimode strategies) to balance measurement error in mail and web towards F2F. Telephone-F2F yielded comparable estimates vis-à-vis the benchmark due to similar measurement error properties and could be implemented directly. The absence of SEs might suggest that the MM designs were successful in mitigating non-observation error differences between designs. More generally, our method could be used by other researchers to evaluate MM redesigns for other surveys.
Web survey bibliography (4086)
- Measuring Nonresponse Bias in Web Surveys: The Role of Health Status; 2014; Zhang, M.
- Providing a Deadline for Response: Results from Two Recent Experiments; 2014; Kaiser, A., Walston, J. T., Medway, R., Ye, C., Tourangeau, R.
- Respondents Playing Fast and Loose?: Antecedents and Consequences of Respondent Speed of Completion; 2014; Thomas, R. K., Barlas, F. M.
- Does Self-Selection Affect Samples' Representativeness in Online Surveys? An Investigation in Online...; 2014; Khazaal, Y., van Singer, M., Chatton, A., Achab, S., Zullino, D., Rothen, S., Khan, R., Billieux, J.,...
- Awareness and Treatment of Alcohol Dependence in Japan: Results from Internet-Based Surveys in Persons...; 2014; Taguchi, Y., Takei, Y., Sasai, R., Murteira, S.
- Internet-based survey on current practice for evaluation, prevention, and treatment of scars, hypertrophic...; 2014; Lumenta, D. B., Siepmann, E., Kamolz, L. P.
- Awareness and correlates of the role of physical activity in breast cancer prevention among Japanese...; 2014; Miyawaki, R., Shibata, A., Ishii, K., Oka, K.
- Barriers and facilitators for participation in a preventive pelvic floor muscle training program from...; 2014; Albers-Heitner, P., Moossdorff-Steinhauser, H., Weemhoff, M., Nieman, F., Berghmans, B.
- Leading Edge Insights: Foundations of Quality 2.0; 2014; Fuguitt, G.
- Current Practices in Management of Hepatocellular Carcinoma in India: Results of an Online Survey; 2014; Kumar, A.
- Inside the Turk Understanding Mechanical Turk as a Participant Pool; 2014; Paolacci, G., Chandler, J.
- Differences in intrapersonal and interactional empowerment between lurkers and posters in health-related...; 2014; Petrovcic, A., Petric, G.
- Test-retest reliability of the International Study of Asthma and Allergies in Childhood questionnaire...; 2014; Yoshida, K., Adachi, Y., Sasaki, M., et al.
- Web-based Emergency Department Patient Satisfaction Surveys May Introduce Potential for Bias; 2014; Broadwater-Hollifield, C., Fair, J., Podolsky, S., et al.
- Process Planning for CNC Machining of Swedish Subcontractors – A Web Survey; 2014; Anderberg, S., Beno, T., Pejryd, L.
- Perceptions on developing clinical practice guidelines for traditional medicine in Korea: Results of...; 2014; Choi, J., Choi, T.-Y., A.; A., Yun, K.-J., A., Lim, H.-J., Lee, J. A., Lee, M. S.
- Recognition of and interventions for Mibyeong (subhealth) in South Korea: a national web-based survey...; 2014; Lee, J., Lee, Y., Dong, S. O., Kim, S.-H., Lee, S.
- Recruiting an Internet Panel Using Respondent-Driven Sampling; 2014; Schonlau, M., Weidmer, B., Kapteyn, A.
- Systematic Review of the Use of Online Questionnaires of Older Adults; 2014; Remillard, M. L., Mazor, K. M., Cutrona, S. L., Gurwitz, J. H., Tjia, J.
- Validating respondents' identity in online samples; 2014; Baker, R., Miller, C., Kachhi-Jiwani, D., Lange, K., Wilding-Brown, L., Tucker, J.
- The relationship between nonresponse strategies and measurement error; 2014; Malhotra, N., Miller, J. M., Wedeking, J.
- Nonresponse and measurement error in an online panel; 2014; Roberts, C., Allum, N., Sturgis, P.
- Estimating the effects of nonresponses in online panels through imputation; 2014; Zhang, W.
- An empirical test of the impact of smartphones on panel-based online data collection; 2014; Drewes, F.
- Professional respondents in nonprobability online panels; 2014; Hillygus, D. S., Jackson, N. M., Young, M.
- Informing panel members about study results; 2014; Scherpenzeel, A., Toepoel, V.
- Determinants of the starting rate and the completion rate in online panel studies; 2014; Goeritz, A.
- The untold story of multi-mode (online and mail) consumer panels; 2014; McCutcheon, A. L., Rao, K., Kaminska, O.
- Online panels and validity; 2014; Groenlund, K., Strandberg, K.
- Assessing representativeness of a probability-based online panel in Germany; 2014; Struminskaya, B., Kaczmirek, L., Schaurer, I., Bandilla, W.
- A critical review of studies investigating the quality of data obtained with online panels based on...; 2014; Callegaro, M., Villar, A., Yeager, D. S., Krosnick, J. A.
- Online panel research: History, concepts, applications and a look at the future; 2014; Callegaro, M., Baker, R., Bethlehem, J., Goeritz, A., Krosnick, J. A., Lavrakas, P. J.
- Motives for joining nonprobability online panels and their association with survey participation behavior...; 2014; Keusch, F., Batinic, B., Mayerhofer, W.
- Improving web survey quality; 2014; Steinmetz, S., Bianchi, S. M., Tijdens, K. G., Biffignandi, S.
- WebSM Study: Survey Software in 2014; 2014; Vehovar, V., Cehovin, G., Mocnik, A.
- Design and Implementation of an Online Questionnaire Tool; 2014; Schaniel, R.
- 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.
- What are the Links in a Web Survey Among Response Time, Quality, and Auto-Evaluation of the Efforts...; 2014; Revilla, M., Ochoa, C.
- Does Age Matter? The Influence of Age on Response Rates in a Mixed-Mode Survey; 2014; Gigliotti, L. M., Dietsch, A.
- Does the Choice of Header Images influence Responses? Findings from a Web Survey on Students’...; 2014; Barth, A.
- Methods and systems for managing an online opinion survey service; 2014; Mcloughlin, M. H., Seton, N., Blesy, K.
- Comparison of the quality estimates in a mixed-mode and a unimode design: an experiment from the European...; 2014; Revilla, M.
- Forget gamification; try writing a humanized survey; 2014; Pettit, A.
- Using respondent tweets to fill in survey gaps; 2014; Murphy, J.
- 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.