Web Survey Bibliography
The apparently easy task of constructing answer formats poses many design decisions with consequences for the reliability and validity of requests. In accordance with Parduccis theoretical framework, the range of scale points and their frequency build a frame for the respondents’ understanding of what was asked and how the answer should be edited. The consequent research shows that answer scales influence respondents’ understanding regarding 1) the meaning of the concept to be measured and 2) their assumptions about the distribution of the associated behaviour or opinion in the population. Consequently, the task of designing answer scales is a complex one. While designing answer scales one should consider the properties of dimension to be measured, the appropriate scale characteristics, the modus of measurement and the characteristics of respondents. This presentation gives an overview of the literature addressing different questions related to the design of answer scales. Is an open ended or a closed answer format appropriate? What is the optimal number of scale points? What about the response order effect? How should labelling be applied? Are fully labelled scales preferable to numbered scales or end-labelled scales? Should the answer scale be polar or bipolar? Should a scale have a middle point and “no opinion” option? While regarding some of these aspects, e.g. numbers of scale points or order effects similar findings and design suggestions are available in the literature (e.g. maxim of reliability in the case of 5-7 scale points), other aspects are controversial. For example prefer some researchers an open ended question format while asking about the frequencies of certain behaviours since the answers are more exact and the context effect of answer scales is absent here. Others discuss the psychological problems associated with an open answer format, e.g. that the respondents round their answers off and build their own answer categories. Considering the presented review of literature the consequences for the design of answer scales and open research questions are summarized.
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Web survey bibliography (4086)
- Web Health Monitoring Survey: A New Approach to Enhance the Effectiveness of Telemedicine Systems; 2017; Romano, M. F.; Sardella, M. V.; Alboni, F.
- Gathering Opinions on Depression Information Needs and Preferences: Samples and Opinions in Clinic Versus...; 2017; Bernstein, M. T.; Walker, J. R.; Sexton, K. A.; Katz, A.; Beatie, B. E.
- Oversampling as a methodological strategy for the study of self-reported health among lesbian, gay and...; 2017; Anderssen, N.; Malterud, K.
- Device and Internet Use among Spanish-dominant Hispanics: Implications for Web Survey Design and Testing...; 2017; Trejo, Y. A. G.; Schoua-Glusberg, A.
- Utjecaj vizualne orientacije skale za odgovaranje i broja stranica web-upitnika na rezultate ispitivanja...; 2017; Malikovic, M.; Svegar, D.; Somodzi, S.
- How to Design a Web Survey Using Spring Boot With MYSQL: a Romanien Network Case Study; 2017; Bucea-Manea-Tonis, Ro.; Bucea-Manea-Tonis, Ra.
- Analyzing Survey Characteristics, Participation, and Evaluation Across 186 Surveys in an Online Opt-...; 2017; Revilla, M.
- Careless Response and Attrition as Sources of Bias in Online Survey Assessments of Personality Traits...; 2017; Meade, A. W.; Ward, M. K.; Alfred, C. M.; Pappalardo, G.; Stoughton, J. W.
- Using Mixed Methods to Research the Professional Development Needs of English Teacher Educators in PCET...; 2017; Eliahoo, R.
- Do Incentives Increase Response Rates to an Internet Survey of American Evaluation Association Members...; 2017; Wilson, L. N.
- Examining Completion Rates in Web Surveys via Over 25,000 Real-World Surveys; 2017; Liu, M.; Wronski, L.
- Data collection mode differences between national face-to-face and web surveys on gender inequality...; 2017; Liu, M.
- Improving survey response rates: The effect of embedded questions in web survey email Invitations; 2017; Liu, M.; Inchausti, N.
- An experimental comparison of web-push vs. paper-only survey procedures for conducting an in-depth health...; 2017; McMaster, H. S.; LeardMann, C. A.; Speigle, S.; Dillman, D. A.
- Demographic Question Placement: Effect on Item Response Rates and Means of a Veterans Health Administration...; 2017; Teclaw, R.; Price, M.; Osatuke, K.
- Effects of Applying Multimedia and Dialogue Box to Web Survey Design; 2017; Chen, H.
- Role of online survey tools in creating temporally accurate Environmental Product Declarations (EPD)...; 2017; Ganguly, I.; Bowers, T.; Pierobon, F.; Eastin, I.
- A test of sample matching using a pseudo-web sample; 2017; Chatrchi, G., Gambino, J.
- A Partially Successful Attempt to Integrate a Web-Recruited Cohort into an Address-Based Sample; 2017; Kott, P. S., Farrelly, M., Kamyab, K.
- Nonprobability sampling as model construction; 2017; Mercer, A. W.
- Comparing acquiescent and extreme response styles in face-to-face and web surveys; 2017; Liu, M.; Conrad, F. G.; Lee, S.
- Comparison of response patterns in different survey designs: a longitudinal panel with mixed-mode and...; 2017; Ruebsamen, N.; Akmatov, M. K.; Castell, S.; Karch, A.; Mikolajczyk, R. T.
- Mobile Research im Kontext der digitalen Transformation; 2017; Friedrich-Freksa, M.
- Kognitives Pretesting; 2017; Neuert, C.
- Grundzüge des Datenschutzrechts und aktuelle Datenschutzprobleme in der Markt- und Sozialforschung; 2017; Schweizer, A.
- Survey mode influence on patient-reported outcome scores in orthopaedic surgery: telephone results may...; 2017; Hammarstedt, J. E.; Redmond, J. M.; Gupta, As.; Dunne, K. F.; Vemula, S. P.; Domb, B. G.
- Marketing survey research best practices: evidence and recommendations from a review of JAMS articles...; 2017; Hulland, J.; Baumgartner, H.; Smith, K. M.
- Comparative analysis of a mobile device and paper as effective survey tools; 2017; Kim, K. J.; Bae, S.; Park, E.
- Enhancing survey participation: Facebook advertisements for recruitment in educational research; 2017; Forgasz, H.; Tan, H.; Leder, G.; McLeod, A.
- Determinants of polling accuracy: the effect of opt-in Internet surveys; 2017; Sohlberg, J.; Gilljam, M.; Martinsson, J.
- Virtual reality meets sensory research; 2017; Depoortere, L.
- Data chunking for mobile web: effects on data quality; 2017; Lugtig, P. J.; Toepoel, V.
- The Failure of the Polls: Lessons Learned from the 2015 UK Polling Disaster; 2017; Sturgis, P.
- Online customer journey analysis: a data science toolbox; 2017; Bonnay, D.
- Article Establishing an Open Probability-Based Mixed-Mode Panel of the General Population in Germany...; 2017; Bosnjak, M.; Dannwolf, T.; Enderle, T.; Schaurer, I.; Struminskaya, B.; Tanner, A.; Weyandt, K.
- PC, phone or tablet? Use, preference and completion rates for web surveys ; 2017; Brosnan, K.; Gruen, B.; Dolnicar, S.
- Comparing data quality and cost from three modes of on-board transit surveys ; 2017; Agrawal, A. W.; Granger-Bevan, S.; W.; Newmark, G. L.; Nixon, H.
- Web survey experiments on matrix questions; 2017; Liu, M.
- Web- and Phone-based Data Collection using Planned Missing Designs; 2017; Revelle, W.; Condon, M. D.; Wilt, J.; French, A. J.; Brown, A.; Elleman, G. L.
- Finding and Investigating Geographical Data Online; 2017; Martin, D.; Cockings, S.; Leung, S.
- CAQDAS at a Crossroads: Affordances of Technology in an Online Environment; 2017; Silver, C.; Bulloch, L. S.
- Online Focus Groups; 2017; Abrams, M. K.; Gaiser, T. J.
- Artificial Intelligence/Expert Systems and Online Research; 2017; Brent, E.
- Improving the Effectiveness of Online Data Collection by Mixing Survey Modes; 2017; Dillman, D. A.; Hao, F.; Millar, M. M.
- Online Survey Software; 2017; Kaczmirek, L.
- Online Survey Design; 2017; To, N.
- Sampling Methods for Online Surveys; 2017; Fricker, R. D.
- Research Design and Tools for Online Research; 2017; Hewson, C. M.
- Overview: Online Surveys; 2017; Vehovar, V.; Lozar Manfreda, K.
- Three Methods for Occupation Coding Based on Statistical Learning; 2017; Geweon, H.; Schonlau, L.; Blohum, M.; Steiner, St.