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 - 2009 (509)
- Creation and Usability Testing of a Web-Based Pre-Scanning Radiology Patient Safety and History Questionnaire...; 2016; Robinson, T. J.; DuVall, S.; Wiggins III, R
- Mixed Research as a Tool for Developing Quantitative Instruments; 2009; Onwuegbuzie, A. J.; Bustamante, R. M.; A. A.Nelson, J. A.
- Slider Scales in Online Surveys; 2009; Cape, P. J.
- User’s Guide to the Advance Release of the 2008-2009 ANES Panel Study ; 2009; DeBell, M.; Krosnick, J. A.; Lupia, A.; Roberts, C.
- The denominator problem: Estimating MSM-specific incidence of sexually transmitted infections and prevalence...; 2009; Marcus, U., Schmidt, A. J., Kollan, C., Hamouda, O.
- Survey Research in the United States: Roots and Emergence 1890-1960 ; 2009; Converse, P. D.
- Practical Considerations in Raking Survey Data; 2009; Battaglia, M. P., Hoaglin, D.C, Franklin, P. D.
- Methods for oversampling rare subpopulations in social surveys; 2009; Kalton, G.
- Start of the LISS panel: Sample and recruitment of a probability-based Internet panel ; 2009; Scherpenzeel, A.
- Comparing response rates in e-mail and paper surveys: A meta-analysis; 2009; Shih, T.-H., Fan, X.
- Recycling and waste minimisation behaviours of the transient student population in Oxford: results of...; 2009; Robertson, S., Walkington, H.
- ESS Handbook for Quality Reports; 2009
- ESS Standard for Quality Reports; 2009
- Guest Blog: More on the Problems with Opt-in Internet Surveys; 2009; Langer, G.
- Psychological Factors Affecting Perceptions of Unsolicited Commercial E-mail; 2009; Morimoto, M., Chang, S.
- Innovations in Social Science Research Methods; 2009; Xenitidou, M., Gilbert, N.
- Where Is the unproctored Internet testing train headed now?; 2009; Tippins, N. T.
- Statistical disclosure control for survey data; 2009; Skinner, C.
- Response format effects on measurement of employment; 2009; Thomas, R. K., Dillman, D. A., Smyth, J. D.
- Preserving the integrity of online testing; 2009; Burke, E.
- Mobile surveys from a technological perspective; 2009; Pferdekämper, T., Batanic, B.
- MarketTools TrueSample; 2009
- ISO 26362 Access panels in market, opinion, and social research-Vocabulary and service requirements; 2009
- Internet alternatives to traditional proctored testing: Where are we now?; 2009; Tippins, N. T.
- From the Editor; 2009; Sackett, P. R.
- Exploring mode effects in a panel survey of new businesses; 2009; Santos, B., DesRoches, D.
- Dirty little secrets of online panels. And how the one you select can make or break your study; 2009
- comScore Media Metrix U.S. Methodlogy. An ARF research review; 2009; Cook, W. A., Pettit, R.
- Can we make official statistics with self-selection web surveys?; 2009; Bethlehem, J.
- Attitudes over time: The psychology of panel conditioning; 2009; Sturgis, P., Allum, N., Brunton-Smith, I.
- Association collaborative effort releases online research definitions, expands membership; 2009
- The Effect of Phrasing Scale Items in Low-Brow or High-Brow Language on Responses; 2009; Blasius, J., Friedrichs, J.
- Question and Questionnaire Design; 2009; Krosnick, J. A., Presser, S.
- Attrition in Consumer Panels; 2009; Tortora, R. D.
- Sample Design for Understanding Society ; 2009; Lynn, P.
- The 2008 Confirmit Annual Market Research Software Survey; 2009; Macer, T., Wilson, S.
- Predicting Tie Strength With Social Media; 2009; Karahalios, K., Gilbert, Er.
- A Special Report from the Advertising Research Foundation - The Foundations of Quality Initiative: A...; 2009; Walker, R., Pettit, R., Rubinson, J.
- A Web-Based Tool for Assessing and Improving the Usefulness of Community Health Assessments; 2009; Stoto, M. A., Straus, S. G., Bohn, C., Irani, P.
- The rise of survey sampling; 2009; Bethlehem, J.
- Using an ABS frame to recruit a probability-based online panel; 2009; DiSogra, C.
- Address Based Sampling: How to Do It, Practical Tips; 2009; Dutwin, D.
- Use of Incentives in Survey Research; 2009; Lavrakas, P. J.
- Stochastic properties of the Internet sample; 2009; Getka-Wilczynska, E.
- Continuous Measurement of Musically-Induced Emotion: A Web Experiment ; 2009; Egermann, H., Nagel, F., Altenmueller, E., Kopiez, R.
- E-epidemiology : Adapting epidemiological methods for the 21st century; 2009; Bexelius, C.
- Web based survey: an emerging tool; 2009; Srivenkataramana, T., Saisree, M.
- The Use of Online Methodologies in Data Collection for Gambling and Gaming Addictions; 2009; Griffiths, M. D.
- Questasy: Online Survey Data Dissemination Using DDI 3; 2009; de Bruijne, M., Amin, A.
- Methodeneffekte von Web-Befragungen: Soziale Erwünschtheit vs. Soziale Entkontextualisierung; 2009; Taddicken, M.