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 (457)
- Handbook of Research Methods in Health Social Sciences; 2017; Liamputtong, P.
- Necessary but Insufficient: Why Measurement Invariance Tests Need Online Probing as a Complementary...; 2017; Meitinger, K.
- Device and Internet Use among Spanish-dominant Hispanics: Implications for Web Survey Design and Testing...; 2017; Trejo, Y. A. G.; Schoua-Glusberg, A.
- Role of online survey tools in creating temporally accurate Environmental Product Declarations (EPD)...; 2017; Ganguly, I.; Bowers, T.; Pierobon, F.; Eastin, I.
- CAQDAS at a Crossroads: Affordances of Technology in an Online Environment; 2017; Silver, C.; Bulloch, L. S.
- Development and Pilot Test of a Mobile Application for Field Data Collection; 2016; Chiappetta, L.; Kerr, M. M.
- A streamlined approach to online linguistic surveys; 2016; Erlewine, M. Y.; Kotek, H.
- The Effects of Vignette Placement on Attitudes Toward Supporting Family Members; 2016; Lau, C. Q., Seltzer, J. A., Bianchi, S. M.
- Using Web Panels to Quantify the Qualitative: The National Center for Health Statistics Research and...; 2016; Scanlon, P. J.
- Bees to Honey or Flies to Manure? How the Usual Subject Recruitment Exacerbates the Shortcomings of...; 2016; Snell, S. A., Hillygus, D. S.
- 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.
- GreenBook Research Industry Trends Report; 2015; Murphy, L. (Ed.)
- Does Sequence Matter in Multimode Surveys: Results from an Experiment; 2014; Wagner, J., Arrieta, J., Guyer, H., Ofstedal, M. B.
- The Use of Cognitive Interviewing Methods to Evaluate Mode Effects in Survey Questions; 2014; Gray, M., Blake, M., Campanelli, P.
- Build your own social network laboratory with Social Lab: a tool for research in social media; 2014; Garaizar, P., Reips, U.-D.
- Using Eye Tracking to Evaluate Email Notifications of Surveys and Online Surveys Collecting Address...; 2014; Olmsted, E. L., Nichols, E. M.
- Correlates of Attrition in the German Internet Panel: Drop-Outs and Sleepers; 2014; Blom, A. G., Beissel-Durrant, G.
- Survey Breakoff in Online Panels; 2014; McCutcheon, A. L.
- Inside the Turk Understanding Mechanical Turk as a Participant Pool; 2014; Paolacci, G., Chandler, J.
- Nonresponse and measurement error in an online panel; 2014; Roberts, C., Allum, N., Sturgis, P.
- Estimating the effects of nonresponses in online panels through imputation; 2014; Zhang, W.
- Professional respondents in nonprobability online panels; 2014; Hillygus, D. S., Jackson, N. M., Young, M.
- Informing panel members about study results; 2014; Scherpenzeel, A., Toepoel, V.
- Determinants of the starting rate and the completion rate in online panel studies; 2014; Goeritz, A.
- The untold story of multi-mode (online and mail) consumer panels; 2014; McCutcheon, A. L., Rao, K., Kaminska, O.
- Online panels and validity; 2014; Groenlund, K., Strandberg, K.
- Assessing representativeness of a probability-based online panel in Germany; 2014; Struminskaya, B., Kaczmirek, L., Schaurer, I., Bandilla, W.
- 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.
- Online panel research: History, concepts, applications and a look at the future; 2014; Callegaro, M., Baker, R., Bethlehem, J., Goeritz, A., Krosnick, J. A., Lavrakas, P. J.
- Motives for joining nonprobability online panels and their association with survey participation behavior...; 2014; Keusch, F., Batinic, B., Mayerhofer, W.
- Targeting the bias – the impact of mass media attention on sample composition and representativeness...; 2014; Steinmetz, S., Oez, F., Tijdens, K. G.
- Exploring selection biases for developing countries - is the web a promising tool for data collection...; 2014; Tijdens, K. G., Steinmetz, S.
- The quality of ego-centered social network data in web surveys: experiments with a visual elicitation...; 2014; Marcin, B., Matzat, U., Snijders, C.
- Switching the polarity of answer options within the questionnaire and using various numbering schemes...; 2014; Struminskaya, B., Schaurer, I., Bosnjak, M.
- Measuring the very long, fuzzy tail in the occupational distribution in web-surveys; 2014; Tijdens, K. G.
- Interest Bias – An Extreme Form of Self-Selection?; 2014; Cape, P. J., Reichert, K.
- Online Qualitative Research – Personality Matters ; 2014; Tress, F., Doessel, C.
- Recent Books and Journals in Public Opinion, Survey Methods, and Survey Statistics; 2014; Callegaro, M.
- Does Gamification Work? - A Literature Review of Empirical Studies on Gamification ; 2014; Hamari, J., Koivisto, J., Sarsa, H.
- The Use of Paradata to Predict Future Cooperation in a Panel Study; 2014; Funke, F., Goeritz, A.
- Pret met panels [Fun online]; 2013; Roberts, A., de Leeuw, E. D., Hox, J., Klausch, L. T., de Jongh, A.
- The Short-term Campaign Panel of the German Longitudinal Election Study 2009. Design, Implementation...; 2013; Steinbrecher, M., Rossmann, J.
- The Future of Social Media, Sociality, and Survey Research; 2013; Hill, C., Dever, J. A.
- Second Life as a Survey Lab: Exploring the Randomized Response Technique in a Virtual Setting; 2013; Richards, A., Dean, E.
- Virtual Cognitive Interviewing Using Skype and Second Life; 2013; Dean, E., Head, B., Swicegood, J. E.
- Social Media, Sociality, and Survey Research; 2013; Hill, C., Dean, E., Murphy, J.
- Investigation of background acoustical effect on online surveys: A case study of a farmers' market...; 2013; Tang, Xi.
- Should the third reminder be sent? The role of survey response timing on web survey results; 2013; Rao, K., Pennington, J.
- Web panel surveys – can they be designed and used in a scientifically sound way?; 2013; Svensson, J.
- Using an Item Response Theory Approach to Measure Survey Mode of Administration Effects: Analysis of...; 2013; Mariano, L. T., Elliott, M. N.