Web Survey Bibliography
Errors can’t be avoided in the assessment of data in (Web) surveys. There are many sources of error on survey statistics resulting in either biased or unbiased estimates. One possible classification (see Groves, Fowler, Couper, Lepkowski, Singer, & Tourangeau, 2004) is to distinguish between representation related sources of error and measurement related errors. With the help of another approach (Sudman, Bradburn, & Schwarz, 1996) we focus on one component of the measurement error, namely formatting. This kind of error happens when there is no optimal option on the rating scale.
Visual analogue scales (VASs)—in our study plain horizontal lines with both ends anchored—are very well suited for Web-based research: They allow fine gradation and differentiation of ratings on a closed-ended continuum. Data from VASs reach—at least with a young and educated student sample—the level of an interval scale (Reips & Funke, 2008). By now it was questionable if certain respondent characteristics had an influence on the quality of data obtained with VASs.
In a Web experiment 1910 respondents from a heterogeneous US sample were asked to locate 15 target values (percentages presented in randomized order) on VASs. We decided to use numbers because they are mentally very well represented. Thus, deviation from target values should be owed to formatting error only. We were able to replicate that data from VASs reach the level of an interval scale (Reips & Funke, 2008) even with a non-student sample. We examined precision of ratings, i.e. the absolute difference between target value and actual rating. Overall, we found a very small formatting error. The mean overall difference was at 1 percentage point. 82% of the ratings were in the interval +/- 2 percentage points. The quality of formatting judgments on VASs was neither affected by sex, age or education nor by Internet experience. We found a statistically significant difference that very fast, spontaneous ratings were marginally less precise, but the effect size was very low.
As the examined respondent characteristics did not show any statistically significant influence on formatting error, we are encouraged to use VASs for surveying samples of the general population.
Conference homepage (abstract)
Web Survey Bibliography - Standards, codes (430)
- The Challenge and Importance of Including Spanish-Dominant Latinos in an Online Panel; 2009; Dennis, J. M., Wells, T., Torres, J.
- Web Panel Studies of the 2008 Election; 2009; Dennis, J. M., Tompson, T.
- Comparison Study of Early Adopter Attitudes and Online Behavior in Probability and Non-Probability Web...; 2009; Dennis, J. M., Osborn, L., Semans, K.
- Summary of KnowledgePanel® Design; 2009; Dennis, J. M.
- Presentation of a Single Item versus a Grid: Effects on the Vitality and Mental Health Scales of the...; 2009; Callegaro, M., Shand-Lubbers, J., Dennis, J. M.
- Computing Response Rates for Probability-Based Web Panels; 2009; DiSogra, C., Callegaro, M.
- Computer-Assisted Audio Recording (CARI): Repurposing a Tool for Evaluating Comparative Instrument Design...; 2009; Edwards, B., Hicks, W., Tourangeau, K., Harris-Kojetin, L., Moss, A.
- Do online translated questionnaires result in higher response rates for patient surveys?; 2009; Boyd, J., Davis, A.
- A comparison of two mixed mode designs: cati-capi and web-cati-capi; 2009; Beukenhorst, D., Wetzels, W.
- Comparison between Liss panel (web) and ESS data (face to face); 2009; Revilla, M., Saris, W. E.
- Is a cell phone really a personal device? Results from the first wave of a mobile phone panel on sharing...; 2009; Fuchs, M., Busse, B.
- Ethical Considerations in the Use of Paradata in Web Surveys; 2009; Couper, M. P., Singer, E.
- Online Analysis and Programmed Disclosure Risk Protection: New Access to Restricted-use Microdata; 2009; McFarland O’Rourke, J., Rush, S. H., Maxwell, C.
- Using the Available On-line Secondary Data in Education and Research Practice; 2009; Perek-Bialas, J.
- Nice portal! But where is the data . . . ? - Experiences of a data archive with offering online access...; 2009; Mauer, R.
- Making Use of Online Survey Documentation & Analysis; 2009; Terwey, M.
- Access to Survey Data on the Internet; 2009; Kolsrud, K.
- Motivating different groups: questionnaire topic and participation rates; 2009; Marchand, M.
- How to cover the general public by Internet interviewing; 2009; Das, M.
- The Internet sample; 2009; Getka-Wilczynska, E.
- Sampling Frame Coverage and Domain Adjustment Procedures for Internet Surveys; 2009; Asan, Z., Ayhan, H. O.
- New Challenges in Sampling: Introduction; 2009; Laaksonen, S.
- Presenting Answers in Random Order: A generic approach for presenting enumeration answers in random...; 2009; Lina, M.
- A Systematic Approach to Debugging in the Blaise Environment: An Author's Perspective; 2009; Sparks, P.
- Paradata and Blaise: A Review of Recent Applications and Research; 2009; O’Reilly, J.
- BlaiseIS at Statistics Netherlands; 2009; de Bolster, G.
- Development of Survey and Case Management facilities for organisations with minimal survey infrastructure...; 2009; Wensing, F.
- Case Management System Based on Wireless Telecommunications; 2009; Kuusela, V., Räikkönen, T., Vikki, K.
- Quality assurance through Computer Audio- Recorded Interviewing (CARI): The Statistics New Zealand Case...; 2009; Seymour, C.
- Be mindful of cellphone interviews; 2009; Anonymous
- If You Provide It, Will They Read It? Response Time Effects in a Choice Experiment; 2009; Vista, A. B., Rosenberger, R. S., Collins, A. R.
- File transfer with built-in editing features; 2009; Erikson, J.
- From paper to internet: Design challenges when mixing modes in longitudinal surveys; 2009; Stax, H.-P., Thomsen, P.
- The Use of Audit Trails in Business Web Surveys; 2009; Snijkers, G., Morren, M.
- Comparing the results of Web surveys on volunteer versus probabilistically selected panels of participants...; 2009; Galesic, M.
- Using Mail Contact to Sample and Encourage Submission of Questionnaire Answers Over the Internet; 2009; Dillman, D. A., Messer, B. L., Millar, M. M.
- Interactive aspects of web surveys; 2009; Conrad, F. G.
- Use of Web surveys in Official Statistics; 2009; Bethlehem, J.
- Donations to charity as incentives in online panels; 2009; Goeritz, A.; Hox, J.
- The Electronic Questionnaire Experience in Business Surveys: mode effects on quality and on response...; 2009; Biffignandi, S., Siesto, G., Zeli, A.
- Reducing Measurement Errors in Surveys; 2009; de Leeuw, E. D.
- Pros and Cons of Internet Surveys Compared to Traditional Survey Methods; 2009; Benjamin, G. D.
- Ethical Issues in Internet Research ; 2009; McKee, H., Porter, J.
- Zero Banks: Coverage Error in List Assisted RDD Samples; 2009; Boyle, J., Bucuvalas, M., Piekarski, L., Weiss, A.
- Combining Data from Probability and Non-Probability Samples Using Pseudo-Weights; 2009; Elliott, M. R.
- The Collected Works of Robert M. Groves, 6 Book Set (Wiley Series in Survey Methodology); 2009; Groves, R. M.
- Complex Surveys: A Guide to Analysis Using R (Wiley Series in Survey Methodology); 2009; Lumley, T. S.
- Methodology of Longitudinal Surveys (Wiley Series in Survey Methodology); 2009; Lynn, P.
- Applied Survey Methods: A Statistical Perspective (Wiley Series in Survey Methodology); 2009; Bethlehem, J.
- Empirical Evaluation of Web Survey Software Tools: Powerful or Friendly?; 2009; Vehovar, V., Berzelak, N., Lozar Manfreda, K., Horvat, T., Debevc, M.