Web Survey Bibliography
Title Characteristics of the Population of Internet Panel Members
Author Boyle, J; Freedner, N.; Fakhouri, T.
Year 2015
Access date 22.08.2016
Abstract
Despite concerns about the non-probability basis for web surveys, an increasing number of studies have found that sample estimates from web surveys compare favorably to those from probability surveys. Aside from the inability to apply probability statistics to these web surveys, potential users worry about how reliable are these estimates.
This paper examines one element that may contribute to the representativeness of web surveys, at least in certain circumstances. Who are the participants and non-participants of these now ubiquitous sources used in population estimates and how similar are they to the population they are meant to represent?
The purpose of this paper is to investigate the actual coverage of Internet panels, generally, among Americanadults. Rather than look at the composition of any one online survey, we consider the characteristics of the population who participate in any web based panel surveys. Since web panels frequently “partner” with other web panel organizations in order to generate samples that are larger, more diverse or more specific than what is available within their panel members, the population who participate in any web panels is more critical to evaluating coverage error and bias of this form of survey than specific coverage and bias errors in individual panels.
A national probability survey of adults was conducted using a dual frame, random digit dialing sample determined participation in Internet survey panels and frequency of participation. Using several classifications for web panelist, we compare the population characteristics of the universe of web panelists compared to the general public. These findings allow us to characterize the degree of coverage and bias associated with the general population of web panelists. We believe that this is the first step in understanding the issues associated with the representativeness and non-representativeness of web survey findings.
This paper examines one element that may contribute to the representativeness of web surveys, at least in certain circumstances. Who are the participants and non-participants of these now ubiquitous sources used in population estimates and how similar are they to the population they are meant to represent?
The purpose of this paper is to investigate the actual coverage of Internet panels, generally, among Americanadults. Rather than look at the composition of any one online survey, we consider the characteristics of the population who participate in any web based panel surveys. Since web panels frequently “partner” with other web panel organizations in order to generate samples that are larger, more diverse or more specific than what is available within their panel members, the population who participate in any web panels is more critical to evaluating coverage error and bias of this form of survey than specific coverage and bias errors in individual panels.
A national probability survey of adults was conducted using a dual frame, random digit dialing sample determined participation in Internet survey panels and frequency of participation. Using several classifications for web panelist, we compare the population characteristics of the universe of web panelists compared to the general public. These findings allow us to characterize the degree of coverage and bias associated with the general population of web panelists. We believe that this is the first step in understanding the issues associated with the representativeness and non-representativeness of web survey findings.
Access/Direct link FCSM Research Conference Homepage (Abstract) / (Full text)
Year of publication2015
Bibliographic typeConferences, workshops, tutorials, presentations
Web survey bibliography - Noncoverage & sampling (851)
- Solving the Nonresponse Problem With Sample Matching?; 2016
- HUFFPOLLSTER: Why Reaching Latinos Is A Challenge For Pollsters; 2016; Jackson, N. M.; Edwards-Levy, A.; Velencia, J.
- Predictive inference for non-probability samples: a simulation study ; 2016; Buelens, B.; Burger, J.; van den Brakel, J.
- Does the Inclusion of Non-Internet Households in a Web Panel Reduce Coverage Bias?; 2016; Eckman, S.
- Quota Controls in Survey Research.; 2016; Gittelman, S. H.; Thomas, R. K.; Lavrakas, P. J.; Lange, V.
- Scientific Surveys Based on Incomplete Sampling Frames and High Rates of Nonresponse; 2016; Fahimi, M.; Barlas, F. M.; Thomas, R. K.; Buttermore, N. R.
- Doing Surveys Online ; 2016; Toepoel, V.
- Doing Online Surveys: Zum Einsatz in der sozialwissenschaftlichen Raumforschung; 2015; Nadler, R.; Petzold, K.; Schoenduwe, R.
- Response Rates and Response Bias in Web Panel Surveys; 2015; Boyle, J.; Berman, L.; Dayton, Ja.; Fakhouri, T.; Iachan, R.; Courtright, M.; Pashupati, K.
- Characteristics of the Population of Internet Panel Members; 2015; Boyle, J; Freedner, N.; Fakhouri, T.
- Internet and Smartphone Coverage in a National Health Survey: Implications for Alternative Modes; 2015; Couper, M. P.; Kelley, J.; Axinn, W.; Guyer, H.; Wagner, J.; West, B. T.
- An Overview of Mobile CATI Issues in Europe; 2015; Slavec, A.; Toninelli, D.
- Using Mobile Phones for High-Frequency Data Collection; 2015; Azevedo, J. P.; Ballivian, A.; Durbin, W.
- Willingness of Online Access Panel Members to Participate in Smartphone Application-Based Research; 2015; Pinter, R.
- Who Has Access to Mobile Devices in an Online Opt-in Panel? An Analysis of Potential Respondents for...; 2015; Revilla, M.; Toninelli, D.; Ochoa, C.; Loewe, G.
- Who Are the Internet Users, Mobile Internet Users, and Mobile-Mostly Internet Users?: Demographic Differences...; 2015; Antoun, C.
- Optimizing the Decennial Census for Mobile – A Case Study; 2015; Nichols, E. M.; Hawala, E. O.; Horwitz, R.; Bentley, M.
- 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 the Go: How Mobile Participants Affect Survey Results; 2015; Barlas, F. M.; Thomas, R. K.
- Variance Estimation for Surveys from Internet Panels ; 2015; Rivers, D.
- Sensitivity Analysis of Bias of Estimates from Web Surveys with Nonrandomized Panel Selection; 2015; Beresovsky, V.
- Detecting Fraud in a Survey Sample Recruited Online; 2015; Brown, D.; Dever, J. A.; Augustson, E.; Squiers, L.
- On Climbing Stairs Many Steps at a Time: The New Normal in Survey Methodology; 2015; Dillman, D. A.
- Mobile Research Methods: Opportunities and challenges of mobile research methodologies. ; 2015; Toninelli, D. (Ed.); Pinter, R.; de Pedraza, P.
- Explorations in Non - Probability Sampling Using the Web; 2015; Brick, J. M.
- On Bias Adjustments for Web Surveys; 2015; Fan, L.; Lou, W.; Landsman, V.
- Web panel surveys – a challenge for official statistics; 2015; Svensson, J.
- Estimation with Non-probability Surveys and the Question of External Validity; 2015; Dever, J. A.; Valliant, R. L.
- Can Non-full-probability Internet Surveys Yield Useful Data? A Comparison with Full-probability Face...; 2015; Simmons, A.D.; Bobo, L. D.
- The Cathie Marsh lecture: What does the failure of the polls tell us about the future of survey research...; 2015; Sturgis, P., Matheson, J.
- Hidden Populations, Online Purposive Sampling, and External Validity: Taking off the Blindfold; 2015; Barrat, M. J.; Ferris, J. A.; Lenton, S.
- Mixed Mode Design Considerations; 2015; Hupp, A.
- Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys 2015; 2015
- Analysis of four recruitment methods for obtaining normative data through a Web-based questionnaire:...; 2015; Nolte, M. T.; Shauver, M. J.; Chung, K. C.
- Doing online research involving university students with disabilities: Methodological issues; 2015; De Cesarei, A.; Baldaro, B.
- 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...
- Correcting for non-response bias in contingent valuation surveys concerning environmental non-market...; 2015; Bonnichsen, O.; Boye Olsen, S.
- An Introduction to Survey Research; 2015; Cowles, E. L.; Nelson, E.
- HUFFPOLLSTER: Pollsters Debate If Modern Surveys Can Be Trusted; 2015; Blumenthal, M.; Edwards-Levy, A.; Velencia, J.
- Using Internet to Recruit Immigrants with Language and Culture Barriers for Tobacco and Alcohol Use...; 2015; Carlini, B. H.; Safioti, L.; Rue, T. C.; Miles, L.
- Online Recruitment Methods for Web-Based and Mobile Health Studies: A Review of the Literature; 2015; Lane, T. S.; Armin, J.; Gordon, Ju. S.
- iTunes Song-Gifting is a Low-Cost, Efficient Recruitment Tool to Engage High-Risk MSM in Internet Research...; 2015; Holland, C. M.; Ritchie, N. D.; Du Bois, S. N.
- Comparing the Similarity of Responses Received from Studies in Amazon’s Mechanical Turk to Studies...; 2015; Bartneck, C.; Duenser, A.; Moltchanova, E.; Zawieska, K.
- Recruiting Online: Lessons From a Longitudinal Survey of Contraception and Pregnancy Intentions of Young...; 2015; Harris, M. L.; Loxton, D.; Wigginton, B.; Lucke, J. C.
- Recruiting for addiction research via Facebook; 2015; Thornton, L. K.; Harris, K.; Baker, A.; Johnson, M.; Kay-Lambkin, F. J.
- Can a non-probabilistic online panel achieve question quality similar to that of the European Social...; 2015; Revilla, M.; Saris, W. E.; Loewe, G.; Ochoa, C.
- Innovative Recruitment Using Online Networks: Lessons Learned From an Online Study of Alcohol and Other...; 2015; Bauermeister, J. A.; Zimmerman, M. A.; Johns, M. M.; Glowacki, P. F.; Stoddard, S. A.; Volz, E. M.
- Probabilistic Web Survey Methodology in Education Centers: An Example in Spanish Schools; 2015; Tapia, J. A., Menendez, J. A.
- Understanding Participation in a Web-Based Measurement Burst Design: Response Metrics and Predictors...; 2015; Griffin, J., Patrick, M. E.
- Facebook as a Tool for Respondent Tracing; 2015; Schneider, S. J., Burke-Garcia, A., Thomas, G.