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 (431)
- Interviewer effects on onliner and offliner participation in the German Internet Panel; 2017; Herzing, J. M. E.; Blom, A. G.; Meuleman, B.
- Millennials and emojis in Spain and Mexico.; 2017; Bosch Jover, O.; Revilla, M.
- Comparing the same Questionnaire between five Online Panels: A Study of the Effect of Recruitment Strategy...; 2017; Schnell, R.; Panreck, L.
- Do distractions during web survey completion affect data quality? Findings from a laboratory experiment...; 2017; Wenz, A.
- A Comparison of Two Nonprobability Samples with Probability Samples; 2017; Zack, E. S.; Kennedy, J. M.
- Targeted letters: Effects on sample composition and item non-response; 2017; Bianchi, A.; Biffignandi, S.
- Oversampling as a methodological strategy for the study of self-reported health among lesbian, gay and...; 2017; Anderssen, N.; Malterud, K.
- Analyzing Survey Characteristics, Participation, and Evaluation Across 186 Surveys in an Online Opt-...; 2017; Revilla, M.
- Comparison of response patterns in different survey designs: a longitudinal panel with mixed-mode and...; 2017; Ruebsamen, N.; Akmatov, M. K.; Castell, S.; Karch, A.; Mikolajczyk, R. T.
- Determinants of polling accuracy: the effect of opt-in Internet surveys; 2017; Sohlberg, J.; Gilljam, M.; Martinsson, J.
- Article Establishing an Open Probability-Based Mixed-Mode Panel of the General Population in Germany...; 2017; Bosnjak, M.; Dannwolf, T.; Enderle, T.; Schaurer, I.; Struminskaya, B.; Tanner, A.; Weyandt, K.
- Effects of Mobile versus PC Web on Survey Response Quality: a Crossover Experiment in a Probability...; 2017; Antoun, C.; Couper, M. P.; G. G.Conrad, F. G.
- Impact of satisficing behavior in online surveys on consumer preference and welfare estimates; 2016; Gao, Z.; House, L. A.; Bi, X.
- Comparing Twitter and Online Panels for Survey Recruitment of E-Cigarette Users and Smokers; 2016; Guillory, J.; Kim, A.; Murphy, J.; Bradfield, B.; Nonnemaker, J.; Hsieh, Y. P.
- Targeted Appeals for Participation in Letters to Panel Survey Members; 2016; Lynn, P.
- Motivated Misreporting in Web Panels; 2016; Bach, R.; Eckman, S.
- Using official surveys to reduce bias of estimates from nonrandom samples collected by web surveys; 2016; Beresovsky, V.; Dorfman, A.; Rumcheva, P.
- A Feasibility Study of Recruiting and Maintaining a Web Panel of People with Disabilities; 2016; Chandler, J.
- Inferences from Internet Panel Studies and Comparisons with Probability Samples; 2016; Lachan, R.; Boyle, J.; Harding, R.
- Exploring the Gig Economy Using a Web-Based Survey: Measuring the Online 'and' Offline Side...; 2016; Robles, B. J.; McGee, M.
- Comparing data quality between online panel and intercept samples; 2016; Liu, M.
- Integration of a phone-based household travel survey and a web-based student travel survey; 2016; Verreault, H.; Morency, C.
- Are Final Comments in Web Survey Panels Associated with Next-Wave Attrition?; 2016; McLauchlan, C.; Schonlau, M.
- Estimation and Adjustment of Self-Selection Bias in Volunteer Panel Web Surveys ; 2016; Niu, Ch.
- Participation in an Intensive Longitudinal Study with Weekly Web Surveys Over 2.5 Years; 2016; Barber, J. S.; Kusunoki, Y.; Gatny, H. H.; Schulz, P.
- The impact of survey duration on completion rates among Millennial respondents ; 2016; Coates, D.; Bliss, M.; Vivar, X.
- Cognitive Probing Methods in Usability Testing – Pros and Cons; 2016; Nichols, E. M.
- Assessing the Accuracy of 51 Nonprobability Online Panels and River Samples: A Study of the Advertising...; 2016; Yang,Y.;Callegaro,M.;Yang,Y.;Callegaro,M.;Chin,K.;Yang,Y.;Villar,A.;Callegaro, M.; Chin, K.; Krosnick...
- Calculating Standard Errors for Nonprobability Samples when Matching to Probability Samples ; 2016; Lee, Ad.; ZuWallack, R. S.
- User Experience and Eye-tracking: Results to Optimize Completion of a Web Survey and Website Design ; 2016; Walton, L.; Ricci, K.; Libman Barry, A.; Eiginger, C.; Christian, L. M.
- Using Web Panels to Quantify the Qualitative: The National Center for Health Statistics Research and...; 2016; Scanlon, P. J.
- Does Changing Monetary Incentive Schemes in Panel Studies Affect Cooperation? A Quasi-experiment on...; 2016; Schaurer, I.; Bosnjak, M.
- Web Probing for Question Evaluation: The Effects of Probe Placement ; 2016; Fowler, S.; Willis, G. B.; Moser, R. P.; Townsend, R. L. M.; Maitland, A.; Sun, H.; Berrigan, D.
- Using Cash Incentives to Help Recruitment in a Probability Based Web Panel: The Effects on Sign Up Rates...; 2016; Krieger, U.
- Making Connections on the Internet: Online Survey Panel Communications ; 2016; Libman Barry, A.; Eiginger, C.; Walton, L.; Ricci, K.
- Evaluating a Modular Design Approach to Collecting Survey Data Using Text Messages ; 2016; West, B. T.; Ghimire, D.; Axinn, W.
- Safety First: Ensuring the Anonymity and Privacy of Iranian Panellists’ While Creating Iran...; 2016; Farmanesh, A.; Mohseni, E.
- Tracking the Representativeness of an Online Panel Over Time ; 2016; Klausch, L. T.; Scherpenzeel, A.
- Non-Observation Bias in an Address-Register-Based CATI/CAPI Mixed Mode Survey; 2016; Lipps, O.
- Bees to Honey or Flies to Manure? How the Usual Subject Recruitment Exacerbates the Shortcomings of...; 2016; Snell, S. A., Hillygus, D. S.
- Thinking Inside the Box Visual Design of the Response Box Affects Creative Divergent Thinking in an...; 2016; Mohr, A. H.; Sell, A.; Lindsay, T.
- Establishing the accuracy of online panels for survey research; 2016; Bruggen, E.; van den Brakel, J.; Krosnick, J. A.
- Adaptive survey designs to minimize survey mode effects – a case study on the Dutch Labor Force...; 2016; Calinescu, M.; Schouten, B.
- What is the gain in a probability-based online panel to provide Internet access to sampling units that...; 2016; Revilla, M.; Cornilleau, A.; Cousteaux, A-S.; Legleye, S; de Pedraza, P.
- Representative web-survey!; 2016; Linde, P.
- The Utility of an Online Convenience Panel for Reaching Rare and Dispersed Populations; 2016; Sell, R.; Goldberg, S.; Conron, K.
- Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk; 2016; Berinsky, A.; Huber, G. A.; Lenz, G. S.
- Setting Up an Online Panel Representative of the General Population The German Internet Panel; 2016; Blom, A. G.; Gathmann, C.; Krieger, U.
- Reducing Underreports of Behaviors in Retrospective Surveys: The Effects of Three Different Strategies...; 2016; Lugtig, P. J.; Glasner, T.; Boeve, A.
- Dropouts in Longitudinal Surveys; 2016; Lugtig, P. J.; De Leeuw, E. D.