Web Survey Bibliography
Grids are commonly used, particularly in web surveys, when multiple items share the same response options. Previous research has found that displaying multiple items in a single grid yields higher correlated responses and less item differentiation compared to using either fewer grid items per screen or having one single item per screen (Tourangeau et al, 2004, Yan, 2005, Toepel et al, 2009). Also, responses in a grid appear to be less consistent when the item definitions are reversed, although the difference is not significant (Callegaro et al, 2009). The aim of our study is to investigate how the number of grid items and screens affect response behavior and data quality given a large number of overall items (12). Users who opt into a survey linked from the Google Maps interface will be shown one of five grid format conditions from a split ballot experiment. Across all groups, users will be presented with only one grid per screen, but the number of screens and grid-items will vary; in the first group, users will be presented with one twelve-item grid, in the second group, two-six item grids, in the third group, three four-item grids, and so forth. Additionally, all twelve grid-items will be randomized across screens and all grids will be presented with the same fully labeled 5-point response scale. We hypothesize that the distribution of answers will differ across experimental conditions and drop-offs and item non-response will increase with larger grids. Additionally, we hypothesize that grids with more items will lead to more measurement error as indicated by a higher rate of inconsistency, especially when the meaning of some grid-items is reversed (i.e confusing vs. simple).
Conference Homepage (abstract)
Web Survey Bibliography - Measurement (1937)
- 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.
- 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.
- 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.
- Using mobile devices to access the realities of youth: How identification with society influences political...; 2013; Smith, M.
- On the Use of Latent Variable Models to Detect Differences in the Interpretation of Vague Quantifiers...; 2013; Griffin, J.
- Managing mobile research: How it's different and why it matters; 2013; Kachhi-Jiwani, D., Tucker, J., Wilding-Brown, L.
- By the Numbers: Theory of adaptation or survival of the fittest?; 2013; Cavallaro, K.
- Designing and conducting business surveys; 2013; Snijkers, G.,Araldsen, G., , Willimack, D. K.Jones, J.
- Battle of the Scales: Understanding Respondent Scale Usage in the US and Abroad; 2013; Courtright, M., Pashupati, K., Pettit, F. A.
- Modular Survey Design: A Bite Size Proposal; 2013; Kelly, F., Stevens, S., Johnson, A.
- Cyborgs vs. Monsters: Assembling Modular Surveys to Create Complete Datasets; 2013; Johnson, E. P., Siluk, L., Tarraf, S.
- Do I Have Your Full Attention?; 2013; Cape, P. J.
- Does Sample Size Still Matter?; 2013; Bakken, D. G., Bond, M.
- Optimizing Surveys for Smartphones: Maximizing Response Rates While Minimizing Bias; 2013; Lattery, K., Park Bartolone, G., Saunders, T.
- Solving the Unintentional Mobile Challenge; 2013; Peterson, G., Mechling, J., LaFrance, J., Ham, G.
- Mobile Research Risk: What Happens to Data Quality When Respondents Use a Mobile Device for a Survey...; 2013; Baker-Prewitt, J.
- Challenges for Researchers Investigating Contraceptive Use and Pregnancy Intentions of Young Women Living...; 2013; Herbert, D. L., Loxton, D., Bateson, D., Weisberg, E., Lucke, J. C.
- Computer science security research and human subjects: Emerging considerations for research ethics boards...; 2013; Buchanan, E. A., Aycock, J., Dexter, S., Dittrich, D., Hvizdak, E. E.
- A standard for test reliability in group research; 2013; Ellis, J. L.
- 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.
