Web Survey Bibliography
Surveys routinely include rating scales that vary considerably in length, from as short as 2 points (e.g., agree/disagree) to moderate lengths (e.g., strongly agree to strongly disagree) to scales as long as 101 points (from 0 to 100 to measure liking or probability). Because the same type of construct is measured in different surveys by scales of different lengths, there appears to be no consensus among investigators about the optimal length of a scale, defined in terms of measurement accuracy (as indicated by reliability and validity), by administration practicality (e.g., how long it takes a respondent to answer the question), and the ratio of the two (measurement accuracy per unit of administration time, in case a large gain in measurement accuracy comes at a small price in terms of administration practicality). Optimal scale length might vary depending on the familiarity of the topic (perhaps people can effectively use longer rating scales to report more refined views on topics about which they have thought a great deal in the past), the nature of verbal labeling of scale points (perhaps full verbal labeling with optimally-chosen labels allows people to use longer scales more effectively, because the meanings of scale points are clearer) and whether the underlying construct is bipolar or unipolar (since a bipolar scale is essentially two unipolar scales joined at the middle). To explore these issues, we conducted a 3-wave web-based panel survey experiment, in which members of a representative sample of American adults (N = 6,055) were randomly assigned to receive various different versions of 20 rating scales. They were also asked theoretically-relevant criteria questions to assess concurrent validity. This paper will report the results of validity assessments to identify the design of rating scales that maximize validity while also maximizing administration practicality (a separate paper will examine reliability).
Conference Homepage (abstract)
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.
