Web Survey Bibliography
Since the early stages of public opinion research, nonresponse has been identified as an important threat to the degree to which our sample can represent the population we are interested in. Researchers have documented a trend of declining response rate over the years. However, the nonresponse rate becomes a concern only when it introduces error or bias into survey results. One way to estimate nonresponse bias is through imputation. Online panels, which maintain a pool of respondents who are invited to participate in research through electronic means, face unique opportunities as well as challenges with regards to nonresponses and their imputations. Using data from a nation-wide online panel, this paper hypothesizes that nonresponse bias may exist due to the common causes shared between response propensity and opinion placements. After testifying the common causes, imputations are made to estimate the missing values. Lastly, the differences between observed distributions on variables of interest and imputed distributions are made to show the scope of nonresponse biases. This paper finds that nonresponse biases may exist in online panels. First, the theoretical model of nonresponse bias was supported because the common-cause pattern was found in the dataset. In other words, response propensity and opinion items that are of interest appeared to share common causes including mostly demographic variables. Second, imputation analyses show that although most of the differences between imputed and measured opinions do not indicate serious biases, there were few cases in which the differences seemed to be critical. The limitations of this study, especially those of the imputation method, are discussed at the end of this chapter. Suggestions for future research are provided too.
Web survey bibliography - Internet access Panels (431)
- Estimating the effects of nonresponses in online panels through imputation; 2014; Zhang, W.
- An empirical test of the impact of smartphones on panel-based online data collection; 2014; Drewes, F.
- 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.
- 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.
- Switching the polarity of answer options within the questionnaire and using various numbering schemes...; 2014; Struminskaya, B., Schaurer, I., Bosnjak, M.
- Interest Bias – An Extreme Form of Self-Selection?; 2014; Cape, P. J., Reichert, K.
- Online Surveys as a Management Tool for Monitoring Multicultual Virtual Team Processes; 2014; Scovotti, C.
- The Use of Paradata to Predict Future Cooperation in a Panel Study; 2014; Funke, F., Goeritz, A.
- Incentives on demand in a probability-based online panel: redemption and the choice between pay-out...; 2014; Schaurer, I., Struminskaya, B., Kaczmirek, L.
- Mixed-devices in a probability based panel survey. Effects on survey measurement error; 2014; Toepoel, V., Lugtig, P. J.
- Topic sensitivity and research design: effects on internet survey respondents' motives; 2014; Albaum, G., Roster, C. A., Smith, S. M.
- Pret met panels [Fun online]; 2013; Roberts, A., de Leeuw, E. D., Hox, J., Klausch, L. T., de Jongh, A.
- PRM144 – An adaptable methodology for the design, implementation and conduct of a web-based survey...; 2013; Yeomans, K., Kawata, A. K., Bassel, M., Burk, C. T., Daniels, S. R., Wilcox, T. K.
- How well do volunteer web panel surveys measure sensitive behaviours in the general population, and...; 2013; Erens, B., Burkill, S., Copas, A., Couper, M. P., Conrad, F.
- The Short-term Campaign Panel of the German Longitudinal Election Study 2009. Design, Implementation...; 2013; Steinbrecher, M., Rossmann, J.
- Understanding Society Innovation Panel Wave 5: results from methodological experiments; 2013; Auspurg, K., Burton, J., Cullinane, C., Delavande, A., Fumagalli, L., Iacovou, M., Jaeckle, A., Kaminska...
- Comparison of US Panel Vendors for Online Surveys; 2013; Cella, D., Craig, B. M., Hays, R. D., Pickard, A. S., Reeve, B. B., Revicki, D. A.
- Research Note: Reducing the Threat of Sensitive Questions in Online Surveys?; 2013; Couper, M. P.
- Is everyone able to use a smartphone in survey research?; 2013; Fernee, H., Sonck, N.
- Web panel surveys – can they be designed and used in a scientifically sound way?; 2013; Svensson, J.
- A standard with quality indicators for web panel surveys: a Swedish example; 2013; Nyfjaell, M.
- Leveraging mobile and online qualitative to get inside shoppers’ heads; 2013; Bryson, J., Ritzo, J.
- Web Panel Representativeness; 2013; Bianchi, A., Biffignandi, S.
- On the Impact of Response Patterns on Survey Estimates from Access Panels; 2013; Enderle, T., Muennich, R., Bruch, C.
- 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.
- Best of Both Worlds? Can we make convenience samples representative?; 2013; Doe, P.
- Evaluating the left‐right dimension: Category Selection Probing conducted in an online access...; 2013; Huefken , V.
- Random versus Systematic Error in a Mixed Mode Online-Telephone Survey; 2013; Hox, J., Scherpenzeel, A., Boeve, A., Boeve, A., de Leeuw, E. D.
- Mobility and Smartphones: a pilot study of travel data collection among experienced and inexperienced...; 2013; Douhou, S., Scherpenzeel, A.
- Mobile devices a way to recruit hard-to-reach groups? Results from a pilot study comparing desk top...; 2013; Toepoel, V., Lugtig, P. J.
- Identifying and Mitigating Satisficing in Web Surveys: Some Experimental Evidence; 2013; Rossmann, J.
- Latent legitimacy: joint effects of religious orientation on the association between values and acceptance...; 2013; Henseler, A. K., Siegers, P., Beckers, T.
- Identifying Satisficing Respondents in Web Surveys: A Comparison of Different Response Time-Based Approaches...; 2013; Rossmann, J.
- Does It Pay Off to Include Non-Internet Households in an Internet Panel? ; 2013; Leenheer, J., Scherpenzeel, A.
- A probability-based web panel for UK policy research: some initial thoughts from a Government survey...; 2013; Littlechild, J.
- Factors Influencing Survey Participation Rates on an Online, Probability-Based Research Panel; 2013; Wiest, D.
- Will Snowball Sampling Leave Your Data in the Cold?; 2013; Cavallaro, K.
- Panel Attrition: Separating Stayers, Sleepers and Other Types of Drop-Out in an Internet Panel; 2013; Lugtig, P. J.
- Innovative Retention Methods in Panel Research: Can SmartPhones Improve Long-Term Panel Participation...; 2013; Dayton, J. J., Dyer, A.
- Predicting Survey Breakoff in Internet Survey Panels; 2013; Al Baghal, T., McCutcheon, A. L., Tsabutashvili, D.
- Online Panels: Recruitment Based on “Hot Topics” – What are the Consequences?; 2013; Andreasson, M., Martinsson, J.
- Responsive Design for Web Panel Data Collection; 2013; Bianchi, A., Biffignandi, S.
- An approach to selecting online respondents; 2013; Terhanian, G.