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 - 2010 (251)
- Running experiments on Amazon Mechanical Turk; 2010; Paolacci, G., Chandler, J., Ipeirotis, P. G.
- Making Good Use of Survey Paradata; 2010; Lynn, P., Nicolaas, G.
- Questionnaire Length, Fatigue Effects and Response Quality Revisited; 2010; Cape, P. J.
- Preventing Satisficing in Online Surveys: A “Kapcha” to Ensure Higher Quality Data...; 2010; Chandler, D., Kapelner, A.
- Game on; 2010; Ewing, T.
- Respondent Engagement: How Much Does it Matter?; 2010
- The Internet and Social Inequalities; 2010; Mannon, S.E.; Witte, J. C.
- Need to Improve Routine HIV Testing of U.S. Veterans in Care: Results of an Internet Survey; 2010; Valdiserri, R. O., Nazi, K., McInnes, D. K., Ross, D., Kinsinger, L.
- The Prevalence of Chronic Pain in United States Adults: Results of an Internet-Based Survey; 2010; Johannes, C. B., Le, T. K., Zhou, X., Johnston, J. A., Dworkin, R. H.
- Response Rates in Organizational Science, 1995–2008: A Meta-analytic Review and Guidelines for...; 2010; Anseel, F., Lievens, F., Schollaert, E., Choragwicka, B.
- Marketing Research: Methodological Foundations; 2010; Iacobucci, D., Churchill, G.A. Jr.
- Computer Assisted Interview Testing Tool (CTT) - a review of new features and how the tool has improved...; 2010; Stark, R., Gatward, R.
- Address-based Sampling Nets Success for KnowledgePanel® Recruitment and Sample Representation; 2010; DiSogra, C.
- A method of automated nonparametric content analysis for social science; 2010; Hopkins, D. J., King, G.
- Developing a web explicit research strategy theory in African universities: a cross-comparison of specific...; 2010; Kirigha, K. A., Neema-A.
- The use of paradata to monitor and manage survey data collection; 2010; Kreuter, F., Couper, M. P., Lyberg, L. E.
- Mitigating Online Survey Nonresponse Error In Aviation Research; 2010; Ison, D. C.
- Optimizing response rates in online surveys; 2010; Kaczmirek, L.
- The Decision Maker's Guide to Online Research; 2010
- Mixed-Method Approaches to Social Network Analysis; 2010; Edwards, G.
- Measuring Intent to Participate and Participation in the 2010 Census and Their Correlates and Trends...; 2010; Pasek, J., Krosnick, J. A.
- Nonresponse and Measurement Error in Mobile Phone Surveys ; 2010; Kennedy, C.
- Wordle; 2010; Feinberg, J.
- What it takes to be a top 100 website; 2010
- Total Survey Error: past, present, and future; 2010; Groves, R. M., Lyberg, L. E.
- There is an app for that! A review of smartphone apps for marketing research; 2010; Michelson, M.
- The who, what, and where of America: Understanding the American Community Survey; 2010; Gaquin, D. A.
- The weirdest people in the world?; 2010; Heine, S. J., Henrich, J., Norenzayan, A.
- The state of online research in the U.S.; 2010; Miller, J.
- The psychology or survey response. An ASA webinar; 2010; Tourangeau, R.
- The psychology of survey response, 2nd Edition; 2010; Tourangeau, R., Bradburn, N. M.
- The multidimensional integral business survey response model; 2010; Bavdaz, M.
- The impact of next and back buttons on time to complete and measurement reliability in computer-based...; 2010; Hays, R. D., Bode, R., Rothrock, N., Riley, W., Cella, D., Gershon, R.
- The Gallup Poll: Public opinion 2009; 2010; Gallup, A. M.
- Surveying cultures: Discovering shared conceptions and sentiments; 2010; Heise, D. R.
- Site-intercpet survey best practices; 2010; Henning, J.
- Sampling: design and analysis, 2nd Edition; 2010; Lohr, S. L.
- 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.
- Real ID. State of The Art Representative and Repeatable Online Samples. Behaviorally Profiled Respondents...; 2010; Gittelman, S. H., Trimarchi, E.
- Randomized response and indirect questioning techniques in surveys; 2010; Chaudhuri, A.
- Protecting and accessing data from the survey of earned doctorates: A workshop summary; 2010; Plewes, T. J.
- Paradata: a new data source from web-administered measures; 2010; Sowan, A. K., Jenkins, L. S.
- Overview of data collection methodology; 2010
- On-the-go and in-the-moment. Mobile research offers speed, immediacy; 2010; Pferdekamper, T.
- Mixed-mode surveys; 2010; Dillman, D. A., Messer, B. L.
- Measuring the group quarters population in the American Community Survey: Interim report; 2010; Marton, K., Voss, P. R.
- Measures of interobserver agreement and reliability; 2010; Shoukri, M. M.
- Machines that lean how to code open ended survey data; 2010; Esuli, A., Sebastiani, F.
- Libraries nationwide receiving ALA-APA Library Salary Survey Invitation; 2010; Grady, J.