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 (6390)
- How Representative are Google Consumer Surveys?: Results From an Analysis of a Google Consumer Survey...; 2013; Krishnamurty, P., Tanenbaum, E., Stern, M. J.
- One Drink or Two: Does Quantity Depicted in an Image Affect Web Survey Responses?; 2013; Charoenruk, N., Stange, M.
- A Comparison Between Screen/Follow Item Format and Yes/No Item Format on a Multi-Mode Federal Survey; 2013; Hernandez,S. J., Arakelyan, S. N., Welch, V. E.
- Using Multiple Modes in Follow-Up Contacts in Random-Digit Dialing Surveys; 2013; Chowdhury, P. P.
- Tablets and Smartphones and Netbooks, Oh My! Effects of Device Type on Respondent Behavior; 2013; Ross, H., Mendelson, J., Lackey, M.
- Impacts of Unit Nonresponse in a Recontact Study of Youth; 2013; Mendelson, J., Viera Jr., L.
- Multi-Mode Survey Administration: Does Offering Multiple Modes at Once Depress Response Rates?; 2013; Newsome, J., Levin, K., Langetieg, P., Vigil, M., Sebastiani, M.
- Responsive Design for Web Panel Data Collection; 2013; Bianchi, A., Biffignandi, S.
- Utilizing the Web in a Multi-Mode Survey; 2013; Venkataraman, L.
- Changing to a Mixed-Mode Design: The Role of Mode in Respondents’ Decisions About Participation...; 2013; Collins, D., Mitchell, M., Toomes, M.
- Comparing the Effects of Mode Design on Response Rate, Representativeness, and Cost Per Complete in...; 2013; Tully, R.
- Internet Response for the Decennial Census – 2012 National Census Test; 2013; Reiser, C.
- The Effects of Pushing Web in a Mixed-Mode Establishment Data Collection; 2013; Ellis, C.
- Using Web Ex to Conduct Usability Testing of an On-Line Survey Instrument; 2013; Stettler, K.
- 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.
- The Effects of Errors in Paradata on Weighting Class Adjustments: A Simulation Study; 2013; West, B. T.
- Using Paradata to Study Response to Within-Survey Requests; 2013; Sakshaug, J. W.
- Paradata for Coverage Research ; 2013; Eckman, S.
- Improving Surveys with Paradata: Analytic Uses of Process Information; 2013; Kreuter, F.
- Theory of adaptation or survival of the fittest?; 2013; Cavallaro, K.
- Online Fundraising Essentials, Second Edition; 2013; Stevenson, S. C.
- Tips for Evaluating Online Effectiveness; 2013; Stevenson, S. C.
- The Digital Divide: The internet and social inequality in international perspective; 2013; Ragnedda, M., Muschert, G.
- Ten questions to ask your online survey provider; 2013; Williams, D.
- Survey quality prediction system 2.0; 2013
- Practical tools for designing and weighting survey samples; 2013; Valliant, R. L., Daver, J. A., Kreuter, F.
- Paradata in web surveys; 2013; Callegaro, M.
- Report Of The AAPOR Task Force On Non-probability sampling; 2013; Baker, R. P., Brick, J. M., Bates, N., Battaglia, M. P., Couper, M. P., Dever, J. A., Gile, K. J., Tourangeau...
- Incentive effects; 2013; Goeritz, A.
- A nationwide web-based freight data collection; 2013; Samimi, A., Mohammadian, A., Kawamura, K.
- Mode Matters: Evaluating Response Comparability in a Mixed-Mode Survey; 2013; Bowyer, B. T., Rogowski, J. C.
- Comparing Survey Results Obtained via Mobile Devices and Computers: An Experiment With a Mobile Web...; 2013; de Bruijne, M., Wijnant, A.
- Cognitive Probes in Web Surveys: On the Effect of Different Text Box Size and Probing Exposure on Response...; 2013; Behr, D., Bandilla, W., Kaczmirek, L., Braun, M.
- The E-Interview in Qualitative Research; 2013; Bampton, R., Cowton, C., Downs, Y.
- Methodological Considerations of Qualitative Email Interviews; 2013; Nehls, K.
- Best Practice in Online Survey Research with Sensitive Topics; 2013; Kays, K., Keith, T. L., Broughal, M. T.
- Research Intentions are Nothing without Technology: Mixed-Method Web Surveys and the Coberen Wall of...; 2013; Ganassali, S., Rodriguez-Santos, C.
- Reducing Response Burden for Enterprises Combining Methods for Data Collection on the Internet; 2013; Vik, T.
- Measuring Wages Worldwide: Exploring the Potentials and Constraints of Volunteer Web Surveys; 2013; Steinmetz, S., Raess, D., Tijdens, K., de Pedraza, P.
- Using Web Surveys for Psychology Experiments: A Case Study in New Media Technology for Research; 2013; Peden, B. F., Tiry , A. M.
- The Distinctiveness of Online Research: Descriptive Assemblages, Unobtrusiveness, and Novel Kinds of...; 2013; Lanfrey, D.
- Sampling, Channels, and Contact Strategies in Internet Survey; 2013; Macrì, E., Tessitore, C.
- Advancing Research Methods with New Technologies; 2013; Sappleton, N.
- Data Quality in PC and Mobile Web Surveys; 2013; Mavletova, A. M.
- PDAs in socio-economic surveys: instrument bias, surveyor bias or both?; 2013; Escobal, J., Benites, S.
- Virtual research assistants: Replacing human interviewers by automated avatars in virtual worlds; 2013; Hasler, B. S., Tuchman, P., Friedman, D.
- Compared to a small, supervised lab experiment, a large, unsupervised web-based experiment on a previously...; 2013; Ryan, R. S., Wilde, M., Crist, S.
- From mixed-mode to multiple devices. Web surveys, smartphone surveys and apps: has the respondent gone...; 2013; Callegaro, M.
- Moving an established survey online – or not?; 2013; Barber, T., Chilvers, D., Kaul, S.
