Web Survey Bibliography
Abstract: Cloud computing represents a new way to deploy computing technology, where dynamically scalable and virtualized resources are provided as a service over the Internet. Amazon Elastic Cloud (EC2) is an example of Infrastructure-as-a-Service that anyone can use today to access infinite computing capacity on demand. This new environment enables collaboration, resources sharing and provides the tools for traceable and reproducible computational research. This model of allocating processing power holds the promise of a revolution in scientific and statistical computing.
Bringing this new era for research and education still requires new software that bridges the gap between the scientist’s everyday tools and the cloud. For instance, making R available as a service in the cloud and allowing its use without any memory or computing constraints would benefit the broad population of statisticians and research professionals. This is what Elastic–R (www.elasticr.net) delivers. It provides a Google docs-like portal and workbench for data analysis that makes using R on the cloud even simpler than using it locally. It enables scientists, educators and students to allocate cloud resources seamlessly work with R engines and use their full capabilities from within any standard web browser.
Features include real time collaboration, sharing and re-using virtual machines, sessions, data, functions, spreadsheets, dashboards, and automatically generated macro enabled Word documents and Excel workbooks which can be synchronized in real-time with R engines on the cloud. Computationally intensive algorithms can easily be run on any number of virtual machines that are controlled from within a standard R session. Elastic-R is also an applications platform that allows anyone to assemble statistical methods and data with interactive user interfaces for the end user. These interfaces and dashboards are created visually, and are automatically published and delivered as simple web applications.
In financial environments, this allows analysts to share common data sources and dashboards and to mirror them in a familiar office environment. In an industrial environment, it allows sharing data and analyses among different production and research sites which may not have the same computing environment. Finally, since the proposed computing architecture uses a cloud as a work horse, large scale and resource demanding calculations can be carried out at a on-demand basis without the need of installing high performance computing systems locally.
Conference Homepage (abstract)
Web survey bibliography (286)
- Paradata as an aide to questionnaire design: Improving quality and reducing burden; 2017; Timm, E.; Stewart, J.; Sidney, I.
- Targeted letters: Effects on sample composition and item non-response; 2017; Bianchi, A.; Biffignandi, S.
- Using Mixed Methods to Research the Professional Development Needs of English Teacher Educators in PCET...; 2017; Eliahoo, R.
- The Failure of the Polls: Lessons Learned from the 2015 UK Polling Disaster; 2017; Sturgis, P.
- Web based health surveys: Using a Two Step Heckman model to examine their potential for population health...; 2016; Morrissey, K.; Kinderman, P.; Pontin, E.; Tai, S.; Schwannauer, M.
- Fieldwork Effort, Response Rate, and the Distribution of Survey Outcomes: A Multilevel Meta-analysis; 2016; Sturgis, P.; Williams, Jo.; Brunton-Smith, I.; Moore, J.
- Gamifying. Not all fun and games; 2016; Stubington, P.; Crichton, C.
- Are interviews costing £0.08 a waste of money? Reviewing Google Surveys for Wisdom of the Crowd...; 2016; Roughton, G.; MacKay, I.
- Observations from Twelve Years of an Annual Market Research Technology Survey; 2016; Macer, T.; Wilson, S.
- FocusVision 2015 Annual MR Technology Report; 2016; Macer, T., Wilson, S.
- Last Year Your Answer Was … The Impact of Dependent Interviewing Wording and Survey Factors on...; 2016; Al Baghal, T.
- Gamifying Questions Using Text Alone; 2016; Cape, P. J.
- Eye-tracking Social Desirability Bias; 2016; Kaminska, O.; Foulsham, T.
- Assessing targeted approach letters: effects in different modes on response rates, response speed and...; 2016; Lynn, P.
- Report of the Inquiry into the 2015 British general election opinion polls; 2016; Sturgis, P., Baker, N., Callegaro, M., Fisher, St., Green, J., Jennings, W., Kuha, J., Lauderdale, B...
- The Validity of Surveys: Online and Offline; 2016; Wiersma, W.
- Revisiting “yes/no” versus “check all that apply”: Results from a mixed modes...; 2016; Nicolaas, G.; Campanelli, P.; Hope, S.; Jaeckle, A.; Lynn, P.
- Adapting Labour Force Survey questions from interviewer-administered modes for web self-completion in...; 2015; Betts, P.; Cubbon, B.
- Recent Books and Journals Articles in Public Opinion, Survey Methods, Survey Statistics, and Big Data...; 2015; Callegaro, M.
- Are Fast Responses More Random? Testing the Effect of Response Time on Scale in an Online Choice Experiment...; 2015; Boerger, T.
- Using equivalence testing to disentangle selection and measurement in mixed modes surveys ; 2015; Cernat, A.
- Polling Error in the 2015 UK General Election: An Analysis of YouGov’s Pre and Post-Election Polls...; 2015; Wells, A.; Rivers, D.
- The Cathie Marsh lecture: What does the failure of the polls tell us about the future of survey research...; 2015; Sturgis, P., Matheson, J.
- Understanding Society Innovation Panel Wave 7: Results from Methodological Experiments; 2015; Blom, A. G.; Burton, J.; Booker, C. L.; Cernat, A.; Fairbrother, M.; Jaeckle, A.; Kaminska, O.; Keusch...
- Email subject lines and response rates to invitations to participate in a web survey and a face-to-face...; 2015; Sappleton, N.; Lourenco, F.
- Validity of Internet-Based Longitudinal Study Data: The Elephant in the Virtual Room; 2015; Pugh, C. A.; Summers, K. M.; Bronsvoort, M. C.; Handel, I. G.; Clements, D. N.
- Challenges with Online Research for Couples and Families: Evaluating Nonrespondents and the Differential...; 2015; Busby, D. M.; Yoshida, Ke.
- Gamification in market research: Increasing enjoyment, participant engagement and richness of data,...; 2015; Bailey, P.; Pritchard, G.; Kernohan, H.
- Going Online with a Face-to-Face Household Panel: Effects of a Mixed Mode Design on Item and Unit Non...; 2015; Burton, J.; Jaeckle, A.; Lynn, P.
- Adapting an interviewer - administered survey for web self - completion in a mixed - mode design ; 2015; Betts, P.; Cubbon, B.
- Technology and Reporting of Daily Activities – Considerations for Analysis of Behaviours in Mixed...; 2015; Fisher, K.; Gershuny, J.
- Measurement Error in Discontinuous Online Survey Panels: Panel Conditioning and Data Quality; 2015; Atkeson, L. R.; Adams, A. N.; Karp, J. A.
- The importance of scale direction between different modes; 2015; Agalioti-sgompou, V.
- The effect of response formats on data quality and comparability across online PC and smartphone surveys...; 2015; Cleary, A.; Allum, N.; Kolbas, V.
- A web-based survey of United Kingdom sedation practice in the intensive care unit; 2015; Yassin, S. M., Yassin, J., Terblanche, M., McKenzie, C. A.
- The Use of Cognitive Interviewing Methods to Evaluate Mode Effects in Survey Questions; 2014; Gray, M., Blake, M., Campanelli, P.
- FocusVision 2014 Annual MR Technology Report; 2014; Macer, T., Wilson, S.
- Do your own online surveys. DYI and self serve market research; 2014; Cary, N.
- Nonprobability Web Surveys to Measure Sexual Behaviors and Attitudes in the General Population: A Comparison...; 2014; Erens, B.; Burkill, S.; Couper, M. P.; C., Clifton, S., Tanton, C., Phelps, A., Datta, J., Mercer,...
- 640 Current trends in management of high-risk prostate cancer in Europe: Results of a web-based survey...; 2014; Briganti, A., Isbarn, H., Ost, P., Ploussard, G., Sooriakumaran, P., Van Den Bergh, R.C.N., Van Oort...
- Is Vague Valid? The Comparative Predictive Validity of Vague Quantifiers and Numeric Response Options...; 2014; Al Baghal, T.
- Improving Survey Response Rates in Online Panels Effects of Low-Cost Incentives and Cost-Free Text Appeal...; 2014; Pedersen, M. J., Nielsen, C. V.
- The role of email addresses and email contact in encouraging web response in a mixed mode design ; 2014; Cernat, A., Lynn, P.
- Mixed-mode surveys of the general population - Results from the European Social Survey mixed-mode experiment...; 2014; Park, A., Humphrey, A.
- Measurement effects between CAPI and Web questionnaires in the UK Household Longitudinal Study; 2014; Lynn, P., Vannieuwenhuyze, J. T. A.
- Role of mode in respondents’ decisions to participate in IP5: findings from a qualitative follow...; 2014; Collins, D., Mitchell, Ma.
- Understanding Society Innovation Panel Wave 6: results from methodological experiments; 2014; Allum, N., Auspurg, K., Blake, M., Booker, C. L., Crossley, T. F., D'ardenne, J., Fairbrother, M., Iacovou...
- The untold story of multi-mode (online and mail) consumer panels; 2014; McCutcheon, A. L., Rao, K., Kaminska, O.
- 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.
- Recent Books and Journals in Public Opinion, Survey Methods, and Survey Statistics; 2014; Callegaro, M.