Web Survey Bibliography
Relevance & Research Question
The market research industry is wedded to quota controls. We apply Age and Gender quotas without a second thought as to why or indeed whether they are doing any good at all. Our argument is that, in the modern online sampling world, a different set of stratifications must be applied and our old assumptions simply do not apply. Why not? The answer, in common with so many of the problems in sampling in online research, lies in the frame. The frame in traditional research was close to the population; therefore a quota controlled random sample would tend to produce samples that, within the quota strata, also contained representative numbers of all other attitudes and behaviours. This is not the case with online access panels.
Methods and Data
Our experiment uses our US panel; the topic, eye colour, is unrelated to Age and Gender but is strongly related to Ethnicity. We have conducted 2 samples. The first strictly controlled on Age, Gender and Region, the second controlled on Ethnicity alone. Our Age Gender Region ‘nat rep’ sample should underestimate the number with brown eyes. The Ethnicity we expect to estimate eye colour extremely well. At the same time a third sample will be drawn which is simply “random enough”. Our expectation is that this sample will also under-perform on eye colour but will equal the findings from “nat rep” sample 1. A second experiment will be undertaken where the variable of interest is unrelated to anything –left- or right-handedness. Our hypothesis is that all three samples will perform equally well.
Results
The results are precisely as predicted.
Added Value
Researchers, particularly in the commercial world, apply quota controls to ensure “representivity” as a matter of practice, they do it because they have been told to, it is part of the folklore of market research. This is not sustainable in a world where we are no longer dealing with essentially incomplete frames. More science and less folklore needs to be applied to make the best of an increasing unscientific world.
Conference Homepage (abstract) / (presentation)
Web Survey Bibliography (467)
- 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.
- Effects of Lotteries on Response Behavior in Online Panels; 2013; Goeritz, A., Luthe, S. C.
- Lotteries and study results in market research online panels; 2013; Goeritz, A., Luthe, S. C.
- Ten questions to ask your online survey provider; 2013; Williams, D.
- An approach to selecting online respondents; 2013; Terhanian, G.
- By the Numbers: Theory of adaptation or survival of the fittest?; 2013; Cavallaro, K.
- Using a web-based survey tool to undertake a Delphi study: Application for nurse education research; 2013; Gill, F. J., Leslie, G. D., Grech, C., Latour, J. M.
- Does one really know?: Avoiding noninformative answers in a reliable way.; 2013; de Leeuw, E. D., Boevee, A., Hox, J.
- Sensitive Topics in PC and Mobile Web Surveys; 2013; Mavletova, A. M., Couper, M. P.
- Sampling online communities: using triplets as basis for a (semi-) automated hyperlink web crawler.; 2013; Veny, Y.
- Propensity Score Weighting – Can Personality Adjust for Selectivity?; 2013; Glantz, A., Greszki, R.
- GESIS Online Panel Pilot: Results from a Probability-Based Online Access Panel; 2013; Kaczmirek, L., Bandilla, W., Schaurer, I., Struminskaya, B., Weyandt, K.
- Innovation in Data Collection: the Responsive Design Approach; 2013; Bianchi, A., Biffignandi, S.
- Break-off and attrition in the GIP amongst technologically experienced and inexperienced participants...; 2013; Blom, A. G., Bossert, D., Clark, V., Funke, F., Gebhard, F., Holthausen, A., Krieger, U., Wachenfeld...
- Nonresponse and Nonresponse Bias in a Probability-Based Internet Panel; 2013; Blom, A. G., Bossert, D., Funke, F., Gebhard, F., Holthausen, A., Krieger, U.
- Rewards - Money for Nothing?; 2013; Cape, P. J., Martin, P.
- Effects of incentive reduction after a series of higher incentive waves in a probability-based online...; 2013; Struminskaya, B., Kaczmirek, L., Schaurer, I., Bandilla, W.
- Timing of Nonparticipation in an Online Panel: The effect of incentive strategies; 2013; Douhou, S., Scherpenzeel, A.
- Measurement effects in mixed-mode panel surveys; 2013; Lugtig, P. J.
- Experiences from a probability-based Internet panel: Sample, recruitment and participation; 2013; Scherpenzeel, A.
- Participation and engagement in web surveys of the general population: An overview of challenges and...; 2013; Roberts, C.
- How Do Lotteries and Study Results Influence Response Behavior in Online Panels?; 2013; Goeritz, A., Luthe, S. C.
- Sample composition discrepancies in different stages of a probability-based online panel; 2013; Bosnjak, M., Haas, I., Galesic, M., Kaczmirek, L., Bandilla, W., Couper, M. P.
- Sensitive topics in PC Web and mobile web surveys: Is there a difference?; 2012; Mavletova, A. M., Couper, M. P.
- Selection bias of internet panel surveys: A comparison with a paper-based survey and national governmental...; 2012; Tsuboi, S. et al.
- Screenwise panel: Frequently Asked Questions; 2012
- Research company spotlight - Mobile surveys; 2012
- NBCU enlists Google, ComScore to track multiscreen Olympics viewing; 2012; Spangler, T.
- More dirty little secrets of online panel research.; 2012
- Google et Médiamétrie créent une audience bimédia; 2012; Gonzales, P.
- Especially for You: Motivating Respondents in an Internet Panel by Offering Tailored Questions; 2012; Oudejans, M.
- The war against unengaged online respondents; 2012; Gittelman, S. H., Trimarchi, E.
- By the Numbers: Lessons for using online panels in B2B research; 2012; Elsner, N.
- Recruiting in an Internet panel using respondent driven sampling; 2012; Schonlau, M.
- Multi-Language Multi-Continent B2B Community Panel: How B2B research can effectively span the world; 2012; Morden, M., Accomando, E.
- WebSM Study: Survey software features overview ; 2012; Vehovar, V.; Cehovin, G.; Kavcic, L.; Lenar, J.
- Web Panels; 2012; Bethlehem, J., Biffignandi, S.
- The Problem of Self-Selection; 2012; Bethlehem, J.,Biffignandi, S.
- Does survey experience affect respondents’ reported level of satisfaction?; 2012; Schultz Christensen, A., Ladenburg, J.
- Evaluation of an online (opt-in) panel for public participation geographic information systems surveys...; 2012; Brown, G., Weber, D., Zanon, D., de Bie, K.
- Panel Conditioning in Online Survey Panels: Problems of Increased Sophistication and Decreased Engagemeent...; 2012; Adams, A. N., Atkeson, L. R., Karp, J. A.
- Surveying Rare Populations Using a Probabilitybased Online Panel; 2012; Peugh, J., Wright, G.
- Recruiting A Probability Sample For An Online Panel: Effects Of Contact Mode, Incentives, And Information...; 2012; Scherpenzeel, A., Toepoel, V.
- Innovation der Online-Datenerhebung für wissenschaftliche Forschungen. Das niederländische MESS-Projekt...; 2012; Das, M.
