Web Survey Bibliography
Substantial effort is expended in the design of surveys, including the amount and type of information they contain. However, we often do not know how involved respondents are in reading and processing the informational content of a survey and making choices, and whether different levels of involvement result in systematic differences in estimated models. To address this issue, we recorded response times for each respondent of an internet-based choice experiment for stream restoration. Response times per survey section and for the entire survey were used as proxies for the amount of involvement in reading information provided or answering choice questions. Response times per survey section fell rapidly, possibly signaling learning, use of heuristics, or attempts to quickly dispel with the survey. Response times were found to be independent of demographics and attitudes. Log-likelihood ratio tests failed to reject the null hypotheses of equal coefficients and scale parameters across response time-partitioned data. However, there exists an association between response times and the increasing learning curve or difficult choice trade-offs, suggesting a heuristic response. Additional research on response time effects and survey design is needed, especially with the rise in electronic surveying media.
D'énormes efforts sont investis dans la conception de sondages, notamment pour déterminer la quantité et le type d'information présentée. Toutefois, nous ne savons pas combien de temps les répondants consacrent à la lecture et au traitement de cette information et au choix des réponses, ni si les divers degrés de participation entraînent ou non des différences systématiques dans les modèles estimés. Pour s'attaquer à cette question, nous avons chronométré les personnes qui ont répondu à un sondage en ligne sur la restauration des cours d'eau. Nous avons utilisé le temps de réponse pour chaque section et pour le sondage au complet comme mesure approximative de l'effort des participants pour lire l'information et répondre aux questions. Pour chaque section, le temps de réponse diminuait rapidement, soit en raison des connaissances heuristiques des répondants, soit en raison de leur désir d'effectuer le sondage le plus rapidement possible. Le temps de réponse s'est révélé indépendant des caractéristiques démographiques et des attitudes des répondants. Des tests du rapport de vraisemblance n'ont pas rejeté les hypothèses nulles de coefficients égaux et de paramètres d'échelle de l'ensemble des données cloisonnées. Toutefois, il existe un lien entre le temps de réponse et la courbe d'apprentissage croissante ou la difficulté des choix, ce qui laisse supposer une réponse heuristique. Il faudrait effectuer davantage de recherche sur les effets du temps consacré pour répondre à un sondage et pour le concevoir, en raison du nombre croissant de sondages en ligne.
Journal homepage (abstract)
Web survey bibliography (281)
- Overview: Online Surveys; 2017; Vehovar, V.; Lozar Manfreda, K.
- Standard Definitions Final Dispositions of Case Codes and Outcome Rates for Surveys; 2016
- Retrospective Measurement of Students’ Extracurricular Activities with a Self-administered Calendar...; 2016; Furthmueller, P.
- Pitfalls, Potentials, and Ethics of Online Survey Research: LGBTQ and Other Marginalized and Hard-to...; 2016; McInroy, L. B.
- Computer-assisted and online data collection in general population surveys; 2016; Skarupova, K.
- A Statistical Approach to Provide Individualized Privacy for Surveys; 2016; Esponda, F.; Huerta, K.; Guerrero, V. M.
- Social Media Analyses for Social Measurement; 2016; Schober, M. F.; Pasek, J.; Guggenheim, L.; Lampe, C.; Conrad, F. G.
- Doing Surveys Online ; 2016; Toepoel, V.
- An Overview of Mobile CATI Issues in Europe; 2015; Slavec, A.; Toninelli, D.
- Utilizing iPads in the Field; 2015; Kiser, P.
- Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys 2015; 2015
- The Web Survey Revolution ; 2015; Murray, D.
- Methodology of the RAND Mid-Term 2014 Election Panel; 2015; Carman, K. G; Pollack, S.
- 28 Questions to Help Buyers of Online Samples; 2015; Cape, P. J.; Phillips, A.; Baker, R.; Cooke, M.; Ribeiro, E.; Terhanian, G.
- Ethical decision-making and Internet research 2.0: Recommendations from the AoIR ethics working committee...; 2015; Markham, A.; Buchanan, E. A.
- Doing online research involving university students with disabilities: Methodological issues; 2015; De Cesarei, A.; Baldaro, B.
- Exploring ethical issues associated with using online surveys in educational research; 2015; Roberts, L. D.; Allen, P. J.
- An Introduction to Survey Research; 2015; Cowles, E. L.; Nelson, E.
- Ethical issues in online research; 2015; James, N.; Busher, H.
- Leading Edge Insights: Foundations of Quality 2.0; 2014; Fuguitt, G.
- Methods and systems for managing an online opinion survey service; 2014; Mcloughlin, M. H., Seton, N., Blesy, K.
- Recent Books and Journals in Public Opinion, Survey Methods, and Survey Statistics; 2014; Callegaro, M.
- Undisclosed Privacy: The Effect of Privacy Rights Design on Response Rates; 2014; Haer, R., Meidert, N.
- Tailoring mode of data collection in longitudinal studies; 2013; Kaminska, O., Lynn, P.
- How do we Know Cognitive Interviewing is Any Good?; 2013; Willis, G. B.
- Quality of Web surveys; 2013; Revilla, M.
- Experiments in Obtaining Data Linkage Consent in Web Surveys ; 2013; Sakshaug, J. W., Kreuter, F.
- Response Burden in Official Business Surveys: Measurement and Reduction Practices of National Statistical...; 2013; Giesen, D., Bavdaz, M., Loefgren, T., Raymond-Blaess, V.
- Internet as a new source of information for the production of official statistics. Experiences of Statistics...; 2013; Heerschap, N.
- A standard with quality indicators for web panel surveys: a Swedish example; 2013; Nyfjaell, M.
- How Mobile Stacks Up to Traditional Online: A Comparison of Studies; 2013; Knowles, R.
- How to make your questionnaire mobile-ready; 2013; Cape, P. J.
- Phish Rising: How Internet Criminals are Undermining the Viability of Online Survey Research…and...; 2013; Kunovic, K.
- Self-Reported Participation in Research Practices Among Survey Methodology Researchers; 2013; Perez-Vergara, K., Smith, C., Lowenstein, C., Ozonoff, A., Martins, Y.
- Ethics, privacy and data security in web-based course evaluation; 2013; Salaschek, M., Meese, C., Thielsch, M.
- Beyond methodology - some ethical implications of "doing research online"; 2013; Heise, N.
- Code Comparison; 2012
- Evaluation procedures for Survey questions; 2012; Saris, W. E.
- Transparency, Access and the Credibility of Survey Research; 2012; Lupia, A.
- Anonymity and Confidentiality; 2012; Tourangeau, R.
- Cognitive Evaluation of Survey Instruments: State of the Science (Art?) and Future Directions; 2012; Willis, G. B.
- How to provide high data quality in online-questionnaires: Setting guidelines in design; 2012; Tries, S., Nebel, S., Blanke, K.
- Comparability of Survey Measurements; 2012; Oberski, D.
- Classification of Surveys; 2012; Stoop, I., Harrison, E.
- Enhancing Web Surveys With New HTML5 Input Types; 2012; Funke, F.
- Why one should incorporate the design weights when adjusting for unit nonresponse using response homogeneity...; 2012; Kott, P. S.
- Assessing the Quality of Survey Data ; 2012; Blasius, J.
- Designing and Doing Survey Research; 2012; Andres, L.
- Using break-offs in web interviews for predicting web response in mixed mode surveys; 2011; Beukenhorst, D.
- Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys 2011; 2011