Web Survey Bibliography
We analyze the results of a national survey collected in two modes: self-administered instrument on the web with personal phone interview follow-up of web non-respondents.We apply regression and implied utility-multiple imputation mode effect adjustments. Since some items may exhibit mode effects, such as social desirability bias, a split-sample design has been built into the study, with 13% of the cases randomized into phone-only condition. Such randomization allows for a rigorous comparison of the item response distributions in the two modes. We analyze the behavioral and attitude items to identify the ones that may have been affected by the mode effect. A logistic model for Yes/No responses or an ordinal logistic model for Likert scales was fit to the data with explanatory variables that included demographic variables and the mode indicator for the subsample of the mode compliers. The regression mode effect adjustments consists of zeroing out the mode variable when forming the predictions based on the estimated regressions, and can be extended to the entire sample. Another mode adjustment is based on econometric framework of implied utilities in logistic regression modeling. We simulated implied utilities of the different responses, followed up by selection of the response with the greatest utility. This is essentially an imputation procedure for the response in the less reliable mode (phone personal interview), and requires the framework of multiple imputation to obtain reliable standard errors. The variables that exhibited the strongest mode effects were found to be the self-reported incidence of donating one’s time to family and neighbors (possible over-reporting due to social desirability bias) andmajor financial problems in the last 5 years (possible under-reporting due to
social desirability bias). The standard errors of the adjusted estimates have gone up, as expected.
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Web survey bibliography - 2013 (465)
- Digging deeper: using implicit tests to define consumers' semantic network; 2013; Riviere, P., Cuny, C., Allain, G., Vereijken, C.
- Conceptualising and evaluating experiences with brands on Facebook; 2013; Smith, S.
- Estimates on the effectiveness of web application firewalls against targeted attacks; 2013; Holm, H., Ekstedt, M.
- Respondent Rewards: Money for Nothing?; 2013; Martin, P.
- How to make your questionnaire mobile-ready; 2013; Cape, P. J.
- Leveraging mobile and online qualitative to get inside shoppers’ heads; 2013; Bryson, J., Ritzo, J.
- A report on the Confirmit Market Research Software Survey 2013; 2013; Macer, T., Wilson, S.
- Thoughts on using the new online qualitative tools; 2013; Freund, N. M.
- Web Panel Representativeness; 2013; Bianchi, A., Biffignandi, S.
- Interactive applets on the Web for methods and statistics; 2013; McClelland, G., Reips, U.-D.
- Economic valuation in Web surveys; A review of the state of the art and best practices; 2013; Menegaki, A. N., Tsagarakis, K. P.
- Can creative web survey questionnaire design improve the response quality?; 2013; Angelovska, J., Mavrikiou, P. M.
- Beyond Satisfaction Questionnaires: “Hacking” the Online Survey; 2013; Evans, A. L.
- Use of mobile devices to answer online surveys: implications for research; 2013; Cunningham, J. A., Neighbors, C., Bertholet, N., Hendershot, C. S.
- Panel Conditioning in Difficult Attitudinal Questions; 2013; Binswanger, J., Schunk, D., Toepoel, V.
- Issues of Coverage and Sampling in Web Surveys for the General Population; 2013; Lynn, P.
- Optimizing quality of response through adaptive survey designs; 2013; Schouten, B., Calinescu, M., Luiten, A.
- Attitudes of Nebraska Residents on Nebraska Water Management; 2013; Dillman, D. A., Edwards, M. L.
- On the Impact of Response Patterns on Survey Estimates from Access Panels; 2013; Enderle, T., Muennich, R., Bruch, C.
- A Comparison of Data Quality Across Modes in a Mixed-Mode Collection of Administrative Records; 2013; Worthy, M., Mayclin, D.
- Reconceptualizing Survey Representativeness for Evaluating and Using Nonprobability Samples; 2013; Fan, D. P.
- To Click, Type, or Drag? Evaluating Speed of Survey Data Input Methods; 2013; Husser, J. A., Husser, J. A.
- Unit Nonresponse and Weighting Adjustments: A Critical Review; 2013; Brick, J. M.
- Internet visual media processing: a survey with graphics and vision applications; 2013; Hu, S.-M., Chen, T., Xu, K., Cheng, M.-M., Martin, R. R.
- Measuring the impact of the Web: Rasch modelling for survey evaluation; 2013; Annoni, P., Weziak-Bialowolska, D., Farhan, H.
- How incentives affect web-based survey response rates of athletic program donors; 2013; Alvarado, G., Callison, C.
- The Effect of Survey Mode on High School Risk Behavior Data: a Comparison between Web and Paper-based...; 2013; Raghupathy, S., Hahn-Smith, S.
- Going online with a face-to-face household panel: initial results from an experiment on the Understanding...; 2013; Jaeckle, A., Lynn, P., Burton, J.
- Targeted response inducement strategies on longitudinal surveys; 2013; Lynn, P.
- Permission email messages significantly increase gambler retention; 2013; Jolley, W., Lee, A., Mizerski, R., Sadeque, S.
- How virtual corporate social responsibility dialogs generate value: A framework and propositions; 2013; Korschun, D., Du, S.
- Customer loyalty to a commercial website: Descriptive meta-analysis of the empirical literature and...; 2013; Toufaily, E., Ricard, L., Perrien, J.
- Discovering interest groups for marketing in virtual communities: An integrated approach; 2013; Wang, K.-Y., Wu, H.-J., Ting, I.-H.
- Understanding service quality in a virtual travel community environment; 2013; Elliot, S., Li, G., Choi, C.
- Research note: E-store image, perceived value and perceived risk; 2013; Chang, E.-C., Tseng, Y.-F.
- The Gamification of Marketing Research; 2013; Donato, P., Link, M. W.
- Gamification Master Class; 2013; Puleston, J.
- Measuring Up: Impact of mobile and segmentation on respondent behaviour; 2013; Luck, K.
- Best of Both Worlds? Can we make convenience samples representative?; 2013; Doe, P.
- Multimode, Global Scale Usage: Understanding respondent scale usage across borders and devices; 2013; Pettit, F. A., Courtright, M.
- Why Big Data is a Small Idea…and Why You Shouldn’t Worry So Much; 2013; Needel, S.
- Advanced Research Methods Training in the UK: Current Provision and Future Strategies; 2013; Moley, S., Wiles, R., Sturgis, P.
- Doing real time research: Opportunities and challenges; 2013; Back, L., Lury, C., Zimmer, R.
- ‘Digital Methods as Mainstream Methodology’: Building capacity in the research community...; 2013; Roberts, S., Hine, C., Morey, Y., Snee, H., Watson, H.
- New social media, new social science?; 2013; Woodfield, K., Morrell, G.
- Digital technology and data collection; 2013; Henriksen, B., Jewitt, C., Price, S., Sakr, M.
- The impact of website content dimension and e-trust on e-marketing effectiveness: The case of Iranian...; 2013; Rahimnia, F., Farzaneh Hassanzadeh, J.
- Survey Breakoffs in a Computer-Assisted Telephone Interview; 2013; McGonagle, K.
- Developing a New Mixed-Mode Methodology For a Provincial Park Camper Survey in British Columbia; 2013; Dyck, B. W.
- Mode effect analysis and adjustment in a split-sample mixed-mode Web/CATI survey; 2013; Kolenikov, S., Kennedy, C.