Web Survey Bibliography
Individuals’ subjective expectations are important in explaining heterogeneity in individual choices, but their elicitation poses some challenges, in particular when one is interested in the subjective probability distribution of an individual. We have developed an innovative visual representation for Internet surveys that has some advantages over previously used formats. In this paper we present our findings from testing this visual representation in the context of individuals’ Social Security expectations. Respondents are asked to allocate a total of 20 balls across seven bins to express what they believe the chances to be that their future Social Security benefits would fall into any one of those bins. Our data come from the Internet survey of respondents to the Health and Retirement Study, a representative survey of the U.S. population aged 51 and older. To contrast the results from the visual format with a previously used format, we divided the sample into two random groups and administered both, the visual format and the more standard percent chance format. Our findings suggest that the main advantage of the visual format is that it generates usable answers for virtually all respondents in the sample while in the percent chance format a significant fraction (about 20 percent) of responses is lost due to inconsistencies. Across various other dimensions, the visual format performs similarly to the percent chance format, leading us to conclude that the bins-and-balls format is a viable alternative that leads to more complete data.
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Web survey bibliography - Public Opinion Quarterly (POQ) (90)
- Necessary but Insufficient: Why Measurement Invariance Tests Need Online Probing as a Complementary...; 2017; Meitinger, K.
- Nonresponse in Organizational Surveying: Attitudinal Distribution Form and Conditional Response Probabilities...; 2017; Kulas, J. T.; Robinson, D. H.; Kellar, D. Z.; Smith, J. A.
- Theory and Practice in Nonprobability Surveys: Parallels between Causal Inference and Survey Inference...; 2017; Mercer, A. W.; Kreuter, F.; Keeter, S.; Stuart, E. A.
- Is There a Future for Surveys; 2017; Miller, P. V.
- Respondent mode choice in a smartphone survey ; 2017; Conrad, F. G., Schober, M. F., Antoun, C., Yan, H. Y., Hupp, A., Johnston, M., Ehlen, P., Vickers, L...
- Effects of Mobile versus PC Web on Survey Response Quality: a Crossover Experiment in a Probability...; 2017; Antoun, C.; Couper, M. P.; G. G.Conrad, F. G.
- The Low Response Score (LRS): A Metric to Locate, Predict, and Manage Hard-to-Survey Populations; 2016; Erdman, C.; Bates, N.
- Targeted Appeals for Participation in Letters to Panel Survey Members; 2016; Lynn, P.
- Fieldwork Effort, Response Rate, and the Distribution of Survey Outcomes: A Multilevel Meta-analysis; 2016; Sturgis, P.; Williams, Jo.; Brunton-Smith, I.; Moore, J.
- Measuring Generalized Trust: An Examination of Question Wording and the Number of Scale Points; 2016; Lundmark, S.; Giljam, M.; Dahlberg, S.
- Social Media Analyses for Social Measurement; 2016; Schober, M. F.; Pasek, J.; Guggenheim, L.; Lampe, C.; Conrad, F. G.
- Do Attempts to Improve Respondent Attention Increase Social Desirability Bias?; 2015; Clifford, S.; Jerit, J.
- Response Rates, Nonresponse Bias, and Data Quality: Results from a National Survey of Senior Healthcare...; 2015; Meterko, M.; Restuccia, J. D.; Stolzmann, K.; Mohr, D.; Brennan, C. W.; Glasgow, J.; Kaboli, P.
- Respondent Screening and Revealed Preference Axioms: Testing Quarantining Methods for Enhanced Data...; 2015; Jones, M. S.; House, L. A.; Zhifeng, G.
- Exploring the Effects of Removing "Too Fast" Responses and Respondents from Web Surveys; 2015; Greszki, R.; Meyer, M.; Schoen, H.
- The Effects of the Direction of Rating Scales on Survey Responses in a Telephone Survey; 2015; Keusch, F., Yan, T.
- Assessing the Potential of Paradata and Other Auxiliary Data for Nonresponse Adjustments; 2014; Krueger, B. S., West, B. T.
- Improving Response Rates and Questionnaire Design for Mobile Web Surveys; 2014; de Bruijne, M., Wijnant, A.
- Assessing Within-Household Selection Methods in Household Mail Surveys; 2014; Olson, K., Stange, M., Smyth, J. D.
- Mobile Technologies for Conducting, Augmenting and Potentially Replacing Surveys: Report of the AAPOR...; 2014; Link, M. W., Murphy, J., Schober, M. F., Buskirk, T. D., Childs, J. H., Tesfaye, C.
- Clicking vs. Dragging: Different Uses of the Mouse and Their Implications for Online Surveys; 2014; Sikkel, D., Steenbergen, R., Gras, S.
- The Effect of Benefit Wording on Consent to Link Survey and Administrative Records in a Web Survey; 2014; Sakshaug, J. W., Kreuter, F.
- Video Content in Web Surveys: Effects on Selection Bias and Validity; 2013; Shapiro-Luft, D., Cappella, J.
- Panel Conditioning in Difficult Attitudinal Questions; 2013; Binswanger, J., Schunk, D., Toepoel, V.
- Clarifying Categorical Concepts in a Web Survey.; 2013; Redline, C. D.
- Recruiting A Probability Sample For An Online Panel: Effects Of Contact Mode, Incentives, And Information...; 2012; Scherpenzeel, A., Toepoel, V.
- Does Giving People Their Preferred Survey Mode Actually Increase Survey Participation Rates?; 2012; Olson, K., Smyth, J. D., Wood, H.
- The changing role of address-based sampling in survey research; 2011; Iannacchione, V. G.
- Measuring americans' issue priorities. A new version of the most important problem question reveals...; 2011; Yeager, D. S., Larson, S. B., Krosnick, J. A., Tompson, T.
- Questions for Surveys: Current Trends and Future Directions; 2011; Schaeffer, N. C., Schaeffer, N. C.
- The Future of Modes of Data Collection; 2011; Couper, M. P.
- The Future of Survey Sampling; 2011; Brick, J. M.
- The Impact of “Forgiving” Introductions on the Reporting of Sensitive Behavior in Surveys...; 2011; Peter, J., Valkenburg, P. M.
- Surveying the General Public over the Internet Using Address-Based Sampling and Mail Contact Procedures...; 2011; Messer, B. L., Dillman, D. A.
- Use of Cognitive Shortcuts in Landline and Cell Phone Surveys; 2011; Everett, S. E., Kennedy, C.
- An Alternative to the Response Rate for Measuring a Survey's Realization of the Target Population; 2011; Skalland, B.
- Can Verbal Instructions Counteract Visual Context Effects in Web Surveys?; 2011; Toepoel, V., Couper, M. P.
- Nonresponse Error, Measurement Error, And Mode Of Data Collection: Tradeoffs in a Multi-mode Survey...; 2011; Sakshaug, J. W., Yan, T., Tourangeau, R.
- A Method for Evaluating Mode Effects in Mixed-mode Surveys; 2011; Vannieuwenhuyze, J., Loosveldt, G., Molenberghs, G.
- Total Survey Error: past, present, and future; 2010; Groves, R. M., Lyberg, L. E.
- Research synthesis. AAPOR report on online panels; 2010; Brick, J. M., Baker, R., Blumberg, S. J., Couper, M. P., Courtright, M., Dennis, J. M., Dillman, D....
- Recruiting probability samples for a multi-mode research panel with Internet and mail components; 2010; Rao, K.
- Cell-Phone-Only Voters in the 2008 Exit Poll and Implications for Future Noncoverage Bias ; 2009; Mokrzycki, M., Keeter, S., Kennedy, C.
- Zero Banks: Coverage Error and Bias in Rdd Samples Based on Hundred Banks with Listed Numbers ; 2009; Boyle, J., Bucuvalas, M., Piekarski, L., Weiss, A.
- National Surveys Via RDD Telephone Interviewing vs. the Internet: Comparing Sample Representativeness...; 2009; Chang, L. C., Krosnick, J. A.
- Impact of T-ACASI on Survey Measurements of Subjective Phenomena ; 2009; Harmon, T., Rogers, S. M., Eggleston, E., Roman, A. M., Villarroel, M. A., Chromy, J. R., Ganapathi,...
- Open-Ended Questions in Web Surveys: Can Increasing the Size of Answer Boxes and Providing Extra Verbal...; 2009; Smyth, J. D., Dillman, D. A., Christian, L. M., McBride, M.
- Web Survey Methods: Introduction; 2009; Couper, M. P., Miller, P. V.
- Social desirability bias in CATI, IVR and Web surveys: The effects of mode and question sensitivity; 2008; Kreuter, F., Presser, S., Tourangeau, R.
- Does a Probability-Based Household Panel Benefit from Assignment to Postal Response as an Alternative...; 2008; Rookey, B. D., Hanway, S., Dillman, D. A.