Web Survey Bibliography
Title Respondents of a follow-up web-based survey
Author Stoddard, S. A.; Amparo, P.; Popick, H.; Yudd, R.; Sujeer, A.; Baath, M.
Year 2016
Access date 13.03.2016
Abstract Background: The use of web-based surveys has increased in recent years, due to an increase in internet access and lower cost. However, studies have found disproportional response to web surveys from male, younger, and better educated adults. Household internet access is higher in Santa Clara County (SCC), California, located in Silicon Valley, than the national figure (87% versus 73%). We conducted a web-based follow-up survey to a random-digit-dial (RDD) telephone survey in SCC, to assess whether demographic biases between web and RDD telephone respondents were still evident in an area with high internet access. Methods: Data are from a survey of adults conducted in 2013-14. The web component was sent to eligible telephone survey respondents (completed the phone survey in English, reported recent internet use, agreed to be re-contacted, and provided a valid email address). Both surveys were conducted by Westat, a research firm headquartered in Rockville, MD. Among 4,186 telephone respondents, 1,176 were eligible and invited to take the web survey (web survey response rate = 41.0%). We compared characteristics of respondents eligible for and completing the web survey (N=482), relative to the telephone survey. Results: Relative to telephone survey respondents, those eligible for the web survey were more likely to be male (47% versus 41%); non-Hispanic White (67% versus 58%), college graduates (68% versus 45%), have household incomes of $75,000 or more (57% versus 45%), US born (73% versus 65%), and younger (mean age, 55 versus 59). Web respondents did not differ substantially by gender from telephone respondents (43% versus 41% for males), but were even more likely to be White (82% versus 58%), college graduates (75% versus 45%), have household incomes of incomes of $75,000 or more (66% versus 45%), and US born (84% versus 65%). Unlike for eligibility, the mean age was similar (both age 59). Conclusion: Unlike previous studies, we found that web survey respondents in an area with high internet access were only slightly more likely to be male but they were of similar age to RDD telephone survey respondents, even though these groups were more likely to be eligible. However, web survey respondents were more likely to be White, well-educated, higher income, and US born. These biases were even more pronounced for those who completed the web survey versus those who were eligible.
Access/Direct link Conference - homepage (Abstract)
Year of publication2015
Bibliographic typeConferences, workshops, tutorials, presentations
Web survey bibliography - 2015 (291)
- 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.
- When will Nonprobability Surveys Mirror Probability Surveys? Considering Types of Inference and Weighting...; 2016; Pasek, J.
- Distractions: The Incidence and Consequences of Interruptions for Survey Respondents ; 2016; Ansolabehere, S.; Schaffner, B. F.
- The Effect of CATI Questions, Respondents, and Interviewers on Response Time; 2016; Olson, K.; Smyth, J. D.
- Linearization Variance Estimators for Mixed ‒ mode Survey Data when Response Indicators are Modeled...; 2016; Demnati, A.
- Adaptive survey designs to minimize survey mode effects – a case study on the Dutch Labor Force...; 2016; Calinescu, M.; Schouten, B.
- What is the gain in a probability-based online panel to provide Internet access to sampling units that...; 2016; Revilla, M.; Cornilleau, A.; Cousteaux, A-S.; Legleye, S; de Pedraza, P.
- Representative web-survey!; 2016; Linde, P.
- Assessing targeted approach letters: effects in different modes on response rates, response speed and...; 2016; Lynn, P.
- New Generation of Online Questionnaires?; 2016; Revilla, M.; Ochoa, C.; Turbina, A.
- The Analysis of Respondent’s Behavior toward Edit Messages in a Web Survey; 2016; Park, Y.
- Refining the Web Response Option in the Multiple Mode Collection of the American Community Survey; 2016; Hughes, T.; Tancreto, J.
- The Utility of an Online Convenience Panel for Reaching Rare and Dispersed Populations; 2016; Sell, R.; Goldberg, S.; Conron, K.
- Setting Up an Online Panel Representative of the General Population The German Internet Panel; 2016; Blom, A. G.; Gathmann, C.; Krieger, U.
- Implementation of Web-Based Respondent Driven Sampling among Men Who Have Sex with Men in Sweden; 2016; Stroemdahl, S.; Lu, X.; Bengtsson, L.; Liljeros, F.; Thorson, A.
- Recommended Practices for the design of business surveys questionnaires; 2016; Macchia, S.
- Web-based versus Paper-based Survey Data: An Estimation of Road Users’ Value of Travel Time Savings...; 2016; Kato, H.; Sakashita, A.; Tsuchiya, Tak.
- Reminder Effect and Data Usability on Web Questionnaire Survey for University Students; 2016; Oishi, T.; Mori, M.; Takata, E.
- Feasibility of using a multilingual web survey in studying the health of ethnic minority youth.; 2016; Kinnunen, J. M.; Malin, M.; Raisamo, S. U.; Lindfors, P. L.; Pere, L. A.; Rimpelae, A. H.
- Respondents of a follow-up web-based survey; 2016; Stoddard, S. A.; Amparo, P.; Popick, H.; Yudd, R.; Sujeer, A.; Baath, M.
- Is One More Reminder Worth It? If So, Pick Up the Phone: Findings from a Web Survey; 2016; Lin-Freeman, L.
- Reducing Underreports of Behaviors in Retrospective Surveys: The Effects of Three Different Strategies...; 2016; Lugtig, P. J.; Glasner, T.; Boeve, A.
- What drives the participation in a monthly research web panel? The experience of ELIPSS, a French random...; 2016; Legleye, S; Cornilleau, A.; Razakamanana, N.
- When Should I Call You? An Analysis of Differences in Demographics and Responses According to Respondents...; 2016; Vicente, P.; Lopes, I.
- The use and positioning of clarification features in web surveys; 2016; Metzler, A., Kunz, T., Fuchs, M.
- Online Surveys are Mixed-Device Surveys. Issues Associated with the Use of Different (Mobile) Devices...; 2016; Toepoel, V.; Lugtig, P. J.
- Mail merge can be used to create personalized questionnaires in complex surveys. ; 2016; Taljaard, M.; Chaudhry, S. H.; Brehaut, J. C.; Weijer, C.; Grimshaw, J. M.
- Electronic and paper based data collection methods in library and information science research: A comparative...; 2016; Tella, A.
- Stable Relationships, Stable Participation? The Effects of Partnership Dissolution and Changes in Relationship...; 2016; Mueller, B.; Castiglioni, L.
- Identifying Pertinent Variables for Nonresponse Follow-Up Surveys. Lessons Learned from 4 Cases in Switzerland...; 2016; Vandenplas, C.; Joye, D.; Staehli, M. E.; Pollien, A.
- The 2013 Census Test: Piloting Methods to Reduce 2020 Census Costs; 2016; Walejko, G. K.; Miller, P. V.
- Methods can matter: Where Web surveys produce different results than phone interviews; 2016; Keeter, S.
- Sunday shopping – The case of three surveys; 2016; Bethlehem, J.
- Will They Stay or Will They Go? Personality Predictors of Dropout in Online Study; 2016; Nestler, S.; Thielsch, M.; Vasilev, E.; Back, M.
- HUFFPOLLSTER: Why Reaching Latinos Is A Challenge For Pollsters; 2016; Jackson, N. M.; Edwards-Levy, A.; Velencia, J.
- Comprehension and engagement in survey interviews with virtual agents; 2016; Conrad, F. G.; Schober, M. F.; Jans, M.; Orlowski, R. A.; Nielsen, D.; Levenstein, R. M.
- Revisiting “yes/no” versus “check all that apply”: Results from a mixed modes...; 2016; Nicolaas, G.; Campanelli, P.; Hope, S.; Jaeckle, A.; Lynn, P.
- Moderators of Candidate Name-Order Effects in Elections: An Experiment; 2016; Kim, Nu.; Krosnick, J. A.; Casasanto, D.
- Predictive inference for non-probability samples: a simulation study ; 2016; Buelens, B.; Burger, J.; van den Brakel, J.
- Equivalence of paper-and-pencil and computerized self-report surveys in older adults; 2016; Weigold, A.; Weigold, I. K.; Drakeford, M. K.; Dykema, S. A.; Smith, C. A.
- Quality of Different Scales in an Online Survey in Mexico and Colombia; 2016; Revilla, M.; Ochoa, C.
- Swapping bricks for clicks: Crowdsourcing longitudinal data on Amazon Turk; 2016; Daly, T. M.; Nataraajan, R.
- A reliability analysis of Mechanical Turk data; 2016; Rouse, S. V.
- Quota Controls in Survey Research.; 2016; Gittelman, S. H.; Thomas, R. K.; Lavrakas, P. J.; Lange, V.
- Computers, Tablets, and Smart Phones: The Truth About Web-based Surveys; 2016; Merle, P.; Gearhart, S.; Craig, C.; Vandyke, M.; Brooks, M. E.; Rahimi, M.
- Scientific Surveys Based on Incomplete Sampling Frames and High Rates of Nonresponse; 2016; Fahimi, M.; Barlas, F. M.; Thomas, R. K.; Buttermore, N. R.
- Taming Big Data: Using App Technology to Study Organizational Behavior on Social Media; 2015; Bail, C. A.
- The Use of a Nonprobability Internet Panel to Monitor Sexual and Reproductive Health in the General...; 2015; Legleye, S; Charrance, G.; Razafindratsima, N.; Bajos, N.; Bohet, A.; Moreau, C.
- Adapting Labour Force Survey questions from interviewer-administered modes for web self-completion in...; 2015; Betts, P.; Cubbon, B.
- ESOMAR/GRBN Online Research Guideline; 2015