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 - 2015 (291)
- Taking MARS Digital; 2015; Melton, E.; Krahn, J.
- A Comparison of the Effects of Face-to-Face and Online Deliberation on Young Students’ Attitudes...; 2015; Triantafillidou, A.; Yannas, P.; Lappas, G.; Kleftodimos, A.
- A Privacy-Friendly Method to Reward Participants of Online-Surveys; 2015; Herfert, M.; Lange, B.; Selzer, A.; Waldmann, U.
- Doing Online Surveys: Zum Einsatz in der sozialwissenschaftlichen Raumforschung; 2015; Nadler, R.; Petzold, K.; Schoenduwe, R.
- Are Fast Responses More Random? Testing the Effect of Response Time on Scale in an Online Choice Experiment...; 2015; Boerger, T.
- The impact of frequency rating scale formats on the measurement of latent variables in web surveys -...; 2015; Menold, N.; Kemper, C. J.
- Investigating response order effects in web surveys using eye tracking; 2015; Karem Hoehne, J.; Lenzner, T.
- Implementation of the forced answering option within online surveys: Do higher item response rates come...; 2015; Decieux, J. P.; Mergener, A.; Neufang, K.; Sischka, P.
- Internet Panels, Professional Respondents, and Data Quality; 2015; Matthijsse, S.; De Leeuw, E. D.; Hox, J.
- Self-administered Questions and Interviewer–Respondent Familiarity; 2015; Rodriguez, L. A., Sana, M., Sisk, B.
- Comparing Food Label Experiments Using Samples from Web Panels versus Mall Intercepts; 2015; Chang, L. C., Lin, C. T. J.
- Translating Answers to Open-ended Survey Questions in Cross-cultural Research: A Case Study on the Interplay...; 2015; Behr, D.
- The impact of gamifying to increase spontaneous awareness; 2015; Cape, P.
- Using eye-tracking to understand how fourth grade students answer matrix items; 2015; Maitland, A.; Sun, H.; Caporaso, A.; Tourangeau, R.; Bertling, J.; Almonte, D.
- Incentive Types and Amounts in a Web-based Survey of College Students; 2015; Krebs, C.; Planty, M.; Stroop, J.; Berzofsky, M.; Lindquist, C.
- 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.
- A Meta-Analysis of Breakoff Rates in Mobile Web Surveys; 2015; Mavletova, A. M.; Couper, M. P.
- The Best of Both Worlds? Combining Passive Data with Survey Data, its Opportunities, Challenges and...; 2015; Duivenvoorde, S.; Dillon, A.
- 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.
- Using Video to Reinvigorate the Open Question; 2015; Cape, P.
- On the Go: How Mobile Participants Affect Survey Results; 2015; Barlas, F. M.; Thomas, R. K.
- The Matrix Lives On: Improving Grids for Online Surveys; 2015; Thomas, R. K.; Barlas, F. M.; Graham, P.; Subias, T.
- 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.
- Survey Treatments and Response Modes: Bayesian Survival Analysis with Competing Risks; 2015; Minato, H.
- Purposefully Mobile: Experimentally Assessing Device Effects in an Online Survey ; 2015; Barlas, F. M.; Thomas, R. K.; Graham, P.
- Using equivalence testing to disentangle selection and measurement in mixed modes surveys ; 2015; Cernat, A.
- What do web survey panel respondents answer when asked “Do you have any other comment?”; 2015; Schonlau, M.
- 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.
- Effect of Web-Based Versus Paper-Based Questionnaires and Follow-Up Strategies on Participation Rates...; 2015; Kilsdonk, E.; van den Heuvel-Eibrink, M. M.; van Dulmen-den Broeder, E.; van der Pal, H. J. H.; van...
- Polling Error in the 2015 UK General Election: An Analysis of YouGov’s Pre and Post-Election Polls...; 2015; Wells, A.; Rivers, D.
- Cell Phone and Face-to-face Interview Responses in Population-based Sur- veys - How Do They Compare?; 2015; Ghandour, L.; Ghandour, B.; Mahfoud, Z.; Mokdad, A.; Sibai, A. M.
- Collecting Health Research Data - Comparing Mobile Phone-assisted Personal Interviewing to Paper-and...; 2015; van Heerden, A. C.; Norris, S. A.; Tollman, S. M.; Richter, L. M.
- The Effects of Questionnaire Completion Using Mobile Devices on Data Quality. Evidence from a Probability...; 2015; Bosnjak, M.; Struminskaya, B.; Weyandt, K.
- Are Sliders Too Slick for Surveys? An Experiment Comparing Slider and Radio Button Scales for Smartphone...; 2015; Aadland, D.; Aalberg, T.
- Evaluation of an Adapted Design in a Multi-device Online Panel: A DemoSCOPE Case Study; 2015; Arn, B.; Klug, S.; Kolodziejski, J.
- Maximizing Data Quality using Mode Switching in Mixed-Device Survey Design: Nonresponse Bias and Models...; 2015; Axinn, W.; Gatny, H. H.; Wagner, J.
- Web Surveys Optimized for Smartphones: Are there Differences Between Computer and Smartphone Users?; 2015; Andreadis, I.
- Measuring Political Knowledge in Web-Based Surveys: An Experimental Validation of Visual Versus Verbal...; 2015; Munzert, S.; Selb, P.
- Validation of the new scale for measuring behaviors of Facebook users: Psycho-Social Aspects of Facebook...; 2015; Bodroza, B.; Jovanovic, T.