Web Survey Bibliography
Data collected through Web surveys, in general, do not adopt traditional probability-based sample designs. Therefore, the inferential techniques used for probability samples may not be guaranteed to be correct for Web surveys without adjustment, and estimates from these surveys are likely to be biased. However, research on the statistical aspect of Web surveys is lacking relative to other aspects of Web surveys. Propensity score adjustment (PSA) has been suggested as an alternative for statistically surmounting inherent problems, namely nonrandomized sample selection, in volunteer Web surveys. However, there has been a minimal amount of evidence for its applicability and performance, and the implications are not conclusive. Moreover, PSA does not take into account problems occurring from uncertain coverage of sampling frames in volunteer panel Web surveys. This study attempted to develop alternative statistical estimation methods for volunteer Web surveys and evaluate their effectiveness in adjusting biases arising
from nonrandomized selection and unequal coverage in volunteer Web surveys. Specifically, the proposed adjustment used a two-step approach. First, PSA was utilized as a method to correct for nonrandomized sample selection, and secondly calibration adjustment was used for uncertain coverage of the sampling frames. The investigation found that the proposed estimation methods showed a potential for reducing the selection and coverage bias in estimates from volunteer panel Web surveys. The combined two-step adjustment not only reduced bias but also mean square errors to a greater degree than each individual adjustment. While the findings from this study may shed some light on Web survey data utilization, there are additional areas to be considered and explored. First, the proposed adjustment decreased bias but did not completely remove it. The adjusted estimates showed a larger variability than the unadjusted ones. The adjusted estimator was no longer in the linear form, but an appropriate variance estimator has not been developed yet. Finally, naively applying the variance estimator for linear statistics highly overestimated the variance, resulting in understating the efficiency of the survey estimates.
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Web survey bibliography - Reports, seminars (231)
- Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys 2016; 2016
- Standard Definitions Final Dispositions of Case Codes and Outcome Rates for Surveys; 2016
- FocusVision 2015 Annual MR Technology Report; 2016; Macer, T., Wilson, S.
- Establishing the accuracy of online panels for survey research; 2016; Bruggen, E.; van den Brakel, J.; Krosnick, J. A.
- Mixing modes of data collection in Swiss social surveys: Methodological report of the LIVES-FORS mixed...; 2016; Roberts, C.; Joye, D.; Staehli, M. E.
- Assessment of Innovations in Data Collection Technology for Understanding Society; 2016; Couper, M. P.
- Report of the Inquiry into the 2015 British general election opinion polls; 2016; Sturgis, P., Baker, N., Callegaro, M., Fisher, St., Green, J., Jennings, W., Kuha, J., Lauderdale, B...
- Evaluating a New Proposal for Detecting Data Falsification in Surveys; 2016; Simmons, K.; Mercer, A. W.; Schwarzer, S.; Courtney, K.
- Computer-assisted and online data collection in general population surveys; 2016; Skarupova, K.
- Predictive inference for non-probability samples: a simulation study ; 2016; Buelens, B.; Burger, J.; van den Brakel, J.
- ESOMAR/GRBN Online Research Guideline; 2015
- App vs. Web for Surveys of Smartphone Users: Experimenting with mobile apps for signal-contingent experience...; 2015; McGeeney, K.; Keeter, S.; Igielnik, R.; Smith, A.; Rainie, L.
- On Climbing Stairs Many Steps at a Time: The New Normal in Survey Methodology; 2015; Dillman, D. A.
- Polling Error in the 2015 UK General Election: An Analysis of YouGov’s Pre and Post-Election Polls...; 2015; Wells, A.; Rivers, D.
- GreenBook Research Industry Trends Report; 2015; Murphy, L. (Ed.)
- Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys 2015; 2015
- 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.
- Understanding Society Innovation Panel Wave 7: Results from Methodological Experiments; 2015; Blom, A. G.; Burton, J.; Booker, C. L.; Cernat, A.; Fairbrother, M.; Jaeckle, A.; Kaminska, O.; Keusch...
- Tips for Creating Web Surveys for Completion on a Mobile Device; 2015; McGeeney, K.
- U.S. Survey Research: Sampling; 2015
- A Comparison of Different Online Sampling Approaches for Generating National Samples; 2014; Heen, M. S. J., Lieberman, J. D., Miethe, T. D.
- FocusVision 2014 Annual MR Technology Report; 2014; Macer, T., Wilson, S.
- The Changing Landscape of Technology and its Effect on Online Survey Data Collection; 2014; Mitchell, N.
- Query on Data Collection for Social Surveys; 2014; Blanke, K., Luiten, A.
- The role of email addresses and email contact in encouraging web response in a mixed mode design ; 2014; Cernat, A., Lynn, P.
- Mixed-mode surveys of the general population - Results from the European Social Survey mixed-mode experiment...; 2014; Park, A., Humphrey, A.
- Mixed-Mode Designs bei Erhebungen mit sensitiven Fragen: Einfluss auf das Teilnahme- und Antwortverhalten...; 2014; Krug, G., Kriwy, P., Carstensen, J.
- Methods and systems for managing an online opinion survey service; 2014; Mcloughlin, M. H., Seton, N., Blesy, K.
- Mobile Technologies for Conducting, Augmenting and Potentially Replacing Surveys: Report of the AAPOR...; 2014; Link, M. W., Murphy, J., Schober, M. F., Buskirk, T. D., Childs, J. H., Tesfaye, C.
- The use of within-subject experiments for estimating measurement effects in mixed-mode surveys ; 2014; Klausch, L. T., Schouten, B., Hox, J.
- Measuring well-being: An analysis of different response scales; 2014; van Beuningen, J., van der Houwen, K., Moonen, L.
- The impact of contact effort and interviewer performance on mode-specific nonresponse and measurement...; 2014; Schouten, B., Cobben, F., van der Laan, J., Arends, J.
- Community Life Survey: Summary of web experiment findings; 2013
- The Short-term Campaign Panel of the German Longitudinal Election Study 2009. Design, Implementation...; 2013; Steinbrecher, M., Rossmann, J.
- Too Fast, Too Straight, Too Weird: Post Hoc Identification of Meaningless Data in Internet ; 2013; Leiner, D. J.
- Postal recruitment into a longitudinal online panel survey. The effects of different number of reminder...; 2013; Martinsson, J.
- The world in 2013. ICT facts and figures; 2013
- Microsoft Security Intelligence Report, Volume 15; 2013
- A Comparison of Results from a Spanish and English Mail Survey: Effects of Instruction Placement on...; 2013; Wang, K., Sha, M.
- Research Note: Reducing the Threat of Sensitive Questions in Online Surveys?; 2013; Couper, M. P.
- Global market research 2013; 2013
- Exploring the Digital Nation: America’s Emerging Online Experience; 2013
- Advantages of a global multimodal print & digital readership survey; 2013; Cour, N., Saint-Joanis, G.
- Australia: building a 21st century readership survey; 2013; Green, A., White, H.
- The new swiss national readership survey: fit for the future ; 2013; Amschler, H., Hoffmann, J.
- ESS Mixed Mode Experiment Results in Estonia (CAWI and CAPI Mode Sequential Design); 2013; Ainsaar, M., Lilleoja, L., Lumiste, K., Roots, A.
- Using smartphones in survey research: a multifunctional tool Implementation of a time use app; a feasability...; 2013; Sonck, N., Fernee, H.
- Adaptive survey designs to minimize survey mode effects. A case study on the Dutch Labour Force Survey...; 2013; Calinescu, M., Schouten, B.
- Optimal Resource Allocation in Adaptive Survey Designs; 2013; Calinescu, M.