Web Survey Bibliography
When will a nonprobability sample look like a probability sample? This key question in survey research has reemerged with the proliferation of new, nonprobability methods for collecting social science data (Baker et al., 2013). Among these, Internet surveys offer myriad advantages in data collection, including reduced costs, faster survey administration, and possibly more accurate self-reports (Chang & Krosnick, 2010; Fricker & Schonlau, 2002; Greenlaw & Brown-Welty, 2009; Wright, 2005) as compared with other survey methods. These surveys also open new research possibilities, allowing for the presentation of experimental stimuli to broad national samples (Couper, 2000; Iyengar, 2011; Skitka & Sargis, 2006). But many of these advantages can only be reaped if data collected from nonprobability samples can be transformed to reflect the public. Inasmuch as this is not the case, there is reason for concern. The majority of Internet surveys use opt-in, nonprobability samples, for which generalizability is not assured (Baker et al., 2010; Couper, 2000).
As nonprobability data collection methods continue to propagate, it becomes increasingly important to demarcate conditions under which data from samples with broad but incomplete coverage and potentially problematic sampling frames will produce results similar to those of probability samples. The ability to account for any differences will likely depend on two critical factors: the type of inference we hope to make and the model we use to translate between the data collected and society as a whole. …
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