Web Survey Bibliography
Relevance & Research Question: Verbal and numeric labels in scalar questions have received a lot of scholarly attention. It is well documented that verbal orientation of scales and adding numbers to anchor the scales influence respondents’ answers. Little is known, however, about switching the scale directions within one questionnaire. This may affect the answers as some respondents miss the fact of the switch (Dillman et al. 2009).
Methods & Data: We test whether switching the verbal orientation of scales and whether the choice of a starting point of numbered scales affect the answers. For that purpose, two experiments will be implemented in the upcoming wave of the GESIS Panel, a probability-based offline recruited mixed-mode (online and mail) panel of the general population in Germany. The first experiment tests the effects of switching the direction of the scale (“strongly agree” to “strongly disagree” and vice versa). The second experiment tests different labeling options. It has three conditions: 1) verbal labeling for end points only and no numbers, 2) fully labeled, starting with 0 and 3) fully labeled, starting with 1.
Results: The field time of the questionnaire starts on December 12, 2013 and ends in the middle of January 2014. The results will be available at that point. The analysis plan for the first experiment is to examine measurement error by comparing means and response distributions. We expect these to differ due to switching as respondents overlook that the order has been reversed. Effects are expected to be more pronounced among respondents who tend to satisfice. Thus, we will compare respondent groups by motivation, cognitive ability, and panel tenure. For the second experiment we will examine the occurrence of a midpoint shift and which of the numbered scales is closer to the scale with polar labels only.
Added Value: This presentation will be of interest to survey researchers who work with online access panels as well as online access panel providers. Often the questionnaire is put together by multiple researchers or clients in which case using multiple scales and various numbering schemes within one questionnaire are very likely.
Web survey bibliography - 2014 (234)
- The relationship between nonresponse strategies and measurement error; 2014; Malhotra, N., Miller, J. M., Wedeking, J.
- Nonresponse and measurement error in an online panel; 2014; Roberts, C., Allum, N., Sturgis, P.
- Estimating the effects of nonresponses in online panels through imputation; 2014; Zhang, W.
- An empirical test of the impact of smartphones on panel-based online data collection; 2014; Drewes, F.
- Professional respondents in nonprobability online panels; 2014; Hillygus, D. S., Jackson, N. M., Young, M.
- Informing panel members about study results; 2014; Scherpenzeel, A., Toepoel, V.
- Determinants of the starting rate and the completion rate in online panel studies; 2014; Goeritz, A.
- The untold story of multi-mode (online and mail) consumer panels; 2014; McCutcheon, A. L., Rao, K., Kaminska, O.
- Online panels and validity; 2014; Groenlund, K., Strandberg, K.
- Assessing representativeness of a probability-based online panel in Germany; 2014; Struminskaya, B., Kaczmirek, L., Schaurer, I., Bandilla, W.
- A critical review of studies investigating the quality of data obtained with online panels based on...; 2014; Callegaro, M., Villar, A., Yeager, D. S., Krosnick, J. A.
- Online panel research: History, concepts, applications and a look at the future; 2014; Callegaro, M., Baker, R., Bethlehem, J., Goeritz, A., Krosnick, J. A., Lavrakas, P. J.
- Motives for joining nonprobability online panels and their association with survey participation behavior...; 2014; Keusch, F., Batinic, B., Mayerhofer, W.
- Improving web survey quality; 2014; Steinmetz, S., Bianchi, S. M., Tijdens, K. G., Biffignandi, S.
- WebSM Study: Survey Software in 2014; 2014; Vehovar, V., Cehovin, G., Mocnik, A.
- Design and Implementation of an Online Questionnaire Tool; 2014; Schaniel, R.
- The Influence of the Answer Box Size on Item Nonresponse to Open-Ended Questions in a Web Survey; 2014; Zuell, C., Menold, N., Koerber, S.
- What are the Links in a Web Survey Among Response Time, Quality, and Auto-Evaluation of the Efforts...; 2014; Revilla, M., Ochoa, C.
- Does Age Matter? The Influence of Age on Response Rates in a Mixed-Mode Survey; 2014; Gigliotti, L. M., Dietsch, A.
- Does the Choice of Header Images influence Responses? Findings from a Web Survey on Students’...; 2014; Barth, A.
- Methods and systems for managing an online opinion survey service; 2014; Mcloughlin, M. H., Seton, N., Blesy, K.
- Comparison of the quality estimates in a mixed-mode and a unimode design: an experiment from the European...; 2014; Revilla, M.
- Forget gamification; try writing a humanized survey; 2014; Pettit, A.
- Using respondent tweets to fill in survey gaps; 2014; Murphy, J.
- Using Paradata to Predict and to Correct for Panel Attrition in a Web-based Panel Survey; 2014; Rossmann, J., Gummer, T.
- Targeting the bias – the impact of mass media attention on sample composition and representativeness...; 2014; Steinmetz, S., Oez, F., Tijdens, K. G.
- Offline Households in the German Internet Panel; 2014; Bossert, D., Holthausen, A., Krieger, U.
- Which fieldwork method for what target group? How to improve response rate and data quality; 2014; Wulfert, T., Woppmann, A.
- Exploring selection biases for developing countries - is the web a promising tool for data collection...; 2014; Tijdens, K. G., Steinmetz, S.
- Evaluating mixed-mode redesign strategies against benchmark surveys: the case of the Crime Victimization...; 2014; Klausch, L. T., Hox, J., Schouten, B.
- The quality of ego-centered social network data in web surveys: experiments with a visual elicitation...; 2014; Marcin, B., Matzat, U., Snijders, C.
- Switching the polarity of answer options within the questionnaire and using various numbering schemes...; 2014; Struminskaya, B., Schaurer, I., Bosnjak, M.
- Measuring the very long, fuzzy tail in the occupational distribution in web-surveys; 2014; Tijdens, K. G.
- Social Media and Surveys: Collaboration, Not Competition; 2014; Couper, M. P.
- Improving cheater detection in web-based randomized response using client-side paradata; 2014; Dombrowski, K., Becker, C.
- Interest Bias – An Extreme Form of Self-Selection?; 2014; Cape, P. J., Reichert, K.
- Online Qualitative Research – Personality Matters ; 2014; Tress, F., Doessel, C.
- Increasing data quality in online surveys 4.1; 2014; Hoeckel, H.
- Moving answers with the GyroScale: Using the mobile device’s gyroscope for market research purposes...; 2014; Luetters, H., Kraus, M., Westphal, D.
- The effectiveness of recruitment strategies on general practitioner's survey response rates - a...; 2014; Pit, S. W., Pyakurel, S., Vo, T.
- Respondent-Driven Sampling of Heterosexuals at Increased Risk of HIV Infection; 2014; Batra, P., Gray, S. C., Krishna, N., Prachand, N., Robinson, W. T., Wejnert, C.
- Two Are Better Than One: The Use of a Mixed-Mode Data Collection to Improve the Electoral Forecast; 2014; de Rada, V. D., Pasadas del Amo, S.
- Social desirability is the same in offline, online, and paper surveys: A meta-analysis; 2014; Dodou, D., de Winter J. C. F.
- The impact of contact effort on mode-specific selection and measurement bias; 2014; Schouten, B., van der Laan, J., Cobben, F.
- Recent Books and Journals in Public Opinion, Survey Methods, and Survey Statistics; 2014; Callegaro, M.
- User-Generated Online Health Content: A Survey of Internet Users in the United Kingdom; 2014; Ziebland, S., Valderas, J., Lupianiez-Villanueva, F., O'Neill, B.
- Confirmation Bias in Web-Based Search: A Randomized Online Study on the Effects of Expert Information...; 2014; Schweiger, S., Oeberst, A., Cress, U.
- Social Media and Online Survey: Tools for Knowledge Management in Health Research ; 2014; Merolli, M., Sanchez, F. J. M., Gray, K.
- Using Online Social Media for Recruitment of Human Immunodeficiency Virus-Positive Participants: A Cross...; 2014; Yuan, P., Bare, M. G., Johnson, M. O., Saberi, P.
- Mobile Technologies for Conducting, Augmenting and Potentially Replacing Surveys: Report of the AAPOR...; 2014; Link, M. W., Murphy, J., Schober, M. F., Buskirk, T. D., Childs, J. H., Tesfaye, C.