Web Survey Bibliography
Effects of number of response options in web surveys: The role of verbal labels
Relevance and research question: Fully labelled agree/disagree rating scales are often used to obtain data pertaining to subjective phenomena in web surveys. Although the link between the number of response options and the quality of information obtained with rating scales is well established, the role of the verbal labels attached to the options is less well studied. The verbal lables define the length and the fineness of a fully labelled rating scale and adding response options may therefore either lengthen the scale and/or make it finer. The aim of the present work it to examine the impact of altering the number and verbal labels of response options on the quality of the information obtained. Fully labelled rating scales with five, seven and nine response options are examined. Verbal labels are either used to lengthen the scales or to make them finer.
Method and data: University students in Germany and Iceland were presented with six questions measuring attitude towards university education in a web survey. Respondents were randomly assigned to six experimental conditions. 1) Five response options with the labels strongly, somewhat and neither/nor, 2) five response options with the lables fully, somewhat and neither nor, 3) seven options with the labels fully, strongly, somewhat and neither nor, 4) seven response options with the labels strongly, somewhat, slightly and neither/nor, 5) seven response options with the labels fully, somewhat, slightly and neither/nor and finally 6) nine response options with the labels fully, strongly, somewhat, slightly and neither/nor.
Results: The results show that the effect of the number of response options on the quality of the information obtained depends on whehter the added response options lengthen the scale or make it finer. A finer scale seems to reduce non-differentiation and extreme response style.
Added value: The findings show that the verbal labels attached to the response options must be taken into account in empirical research on the optimal number of response options.
GOR Homepage (abstract) / (presentation)
Web Survey Bibliography - Conferences, workshops, tutorials, presentations (3066)
- The challenge of a mixed-mode design survey and new IT tools application: the case of the Italian Structure...; 2013; Cardinaleschi, S., De Santis, S., Rocci, F., Spinelli, V.
- MOTUS: Modular online Time-Use Survey; 2013; Joeri, M., Ignace, G., van Tienoven, T. P., Djiwo, W.
- The Design of the Online Questionnaire of the Italian Population Census ; 2013; Tininini, L., Virgillito, A.
- Experiments in Obtaining Data Linkage Consent in Web Surveys ; 2013; Sakshaug, J. W., Kreuter, F.
- The behaviour of respondents while filling in a web questionnaire: the case of the Italian business...; 2013; Masselli, M., Nuccitelli, A.
- A web-based Census of services: an ISTAT evolutionary study ; 2013; Cesaro, A., Palazzi, B., Paterniti, M., Ranaldi, P.
- A web based management system for addressing census complexity: the Italian experience; 2013; Bruno, M., Giacummo, M., Silipo, M., Vaste, G.
- Response Burden in Official Business Surveys: Measurement and Reduction Practices of National Statistical...; 2013; Giesen, D., Bavdaz, M., Loefgren, T., Raymond-Blaess, V.
- Factors affecting the decision to participate in the internet option for the 2010 Census of Korea ; 2013; Lee, E., Kim, S.
- Internet as a new source of information for the production of official statistics. Experiences of Statistics...; 2013; Heerschap, N.
- Web panel surveys – can they be designed and used in a scientifically sound way?; 2013; Svensson , J.
- A standard with quality indicators for web panel surveys: a Swedish example; 2013; Nyfjaell, M.
- Web Panels for Official Statistics? ; 2013; Bethlehem, J., Cobben, F.
- Assessing Nonresponse Bias in the Green Technologies and Practices Survey; 2013; Meekins, B., Sverchkov, M., Stang, S.
- Using an Item Response Theory Approach to Measure Survey Mode of Administration Effects: Analysis of...; 2013; Mariano, L. T., Elliott, M. N.
- The Role of Mode Preference Questions in Predicting Mode-Specific Response Propensities; 2013; Lynn, P., Kaminska, O.
- How Does Online Survey Mode Affect Answers to Customer Feedback Loyalty Surveys?; 2013; Gupta, A., Lee, J.
- Using Internet Panel Surveys for Behavioral Health Surveillance; 2013; Gotway Crawford, C., Okoro, C. A., Dhingra, S., Akcin, H., Zhao, G., Ford, D., Pierannunzi, C.
- Model-Based Mode of Data Collection Switching from Internet to Mail in the American Community Survey; 2013; Chesnut, J.
- Estimating Mode Effects Without Bias: A Randomized Experiment to Compare Mode Effects Between Face-to...; 2013; Rivers, D., Vavreck, L.
- How Mobile Stacks Up to Traditional Online: A Comparison of Studies; 2013; Knowles, R.
- Respondent Rewards: Money for Nothing?; 2013; Martin, P.
- Did I Do That? How Trap Questions Can Hurt Data Quality; 2013; Phillips, K.
- Web Coverage in the UK and its Potential Impact on General Population Web Surveys; 2013; Callegaro, M.
- Issues of Coverage and Sampling in Web Surveys for the General Population; 2013; Lynn, P.
- Gamification Master Class; 2013; Puleston, J.
- Research Communities in Asia Pacific: A review of similarities and contrasts; 2013; Poynter, R.
- Measuring Up: Impact of mobile and segmentation on respondent behaviour; 2013; Luck, K.
- Best of Both Worlds? Can we make convenience samples representative?; 2013; Doe, P.
- Multimode, Global Scale Usage: Understanding respondent scale usage across borders and devices; 2013; Pettit, F. A., Courtright, M.
- Why Big Data is a Small Idea…and Why You Shouldn’t Worry So Much; 2013; Needel, S.
- Mode effect analysis and adjustment in a split-sample mixed-mode Web/CATI survey; 2013; Kolenikov, S., Kennedy, C.
- Exploring factors associated with respondent mode choice for surveys using mobile devices.; 2013; Walton, L.
- Responsive design for mixed-mode panel data; 2013; Bianchi, A., Biffignandi, S.
- Adjusting for bias in a mixed-mode CAWI survey on University students ; 2013; Clerici, R., Giraldo, A.
- Comparative analysis of data from web and face-to-face surveys. A case study on e-commerce in young...; 2013; Cappello, C., Pellegrino, D.
- Insights into Action Profiling shopping occasions for retailers through mobile and online research; 2013; Churkina, O., Morris, T.
- Mobilizing your Branded Panel: Panel data quality during the smartphone transition; 2013; Kugel, C., Brien, D., Blechman, J.
- Evaluating the left‐right dimension: Category Selection Probing conducted in an online access...; 2013; Huefken , V.
- From Face‐to‐face to Web: Consequences for Measurement of Complex and Open‐ended Questions...; 2013; Villar, A., Fitzgerald, R., Martin, P., Harrison, E., Gatrrell, L.
- Computers, Tablet & Smart Phones: The Truth about Web‐based Surveys; 2013; Merle, P., Gearhart, S., Craig, C., Rahimi, M., Brooks, M. E., Vandyke, M.
- Explaining Interview Duration in Web Surveys on Political Attitudes and Behavior: A Multilevel Approach...; 2013; Gummer, T., Rossmann, J.
- An Examination of the Relationship Between Pretest Method Results and Data Quality; 2013; Maitland, A.
- Associations Between Interactional Indicators of Problematic Questions and Systems for Coding Question...; 2013; Dykema, J., Schaeffer, N. C., Garbarski, D.
- The Technology Behind Mobile Research: Browsers vs. Apps ; 2013; Macer, T.
- Methodological, legal and technical perspectives on the feasibility of web survey paradata in German...; 2013; Sattelberger, S.
- Specific mixed-mode methodologies to include sensory disabled people in quantitative surveys; 2013; Sebastien, F., Marc, J., Patrick, I.
- An imputation approach for analyzing mixed-mode surveys; 2013; Kim, J. K., Park, S., Kim, S. Y.
- Investigating the Bias of Alternative Statistical Inference Methods in Sequential Mixed-Mode Surveys; 2013; Suzer-Gurtekin, Z., Heeringa, S. G., Valliant, R. L.
- Random versus Systematic Error in a Mixed Mode Online-Telephone Survey; 2013; Hox, J., Scherpenzeel, A., Boeve, A., Boeve, A., de Leeuw, E. D.