Web Survey Bibliography
Non-response is only one of a few things that can go wrong in a survey. There are many more areas of data collection and data processing that can introduce errors and thus affect the quality of results. The definitive result of all survey errors is a discrepancy between the survey estimate and the population characteristic to be estimated. This discrepancy is called the total survey error. Essentially two main categories can be pointed out contributing to this total error: sampling and nonsampling errors. Sampling errors are due to the sampling design. They are introduced when estimates are based on a sample and not on a total enumeration of the population. Such errors can in theory be avoided by a complete enumeration of the population. However, only a part of the population is used for estimating population characteristics. Nonsampling errors may occur even if the whole population is investigated. They denote errors made during the process of obtaining answers to questions asked. Nonsampling errors can arise from both observation and nonobservation errors. Non-observation errors are errors made when the intended measurements are not obtained. Undercoverage occurs when elements of the target population do not have a corresponding entry in the sampling frame. These population members cannot even be contacted. A type of non-observation error is non-response. This type of situation occurs when the sampled person does not provide the required information.
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Web survey bibliography (4086)
- Media tracker; 2012
- Measuring the quality of governmental websites in a controlled versus an online setting with the ‘...; 2012; Elling, S., Lentz, L., de Jong , M., van den Bergh, H.
- Measuring modern media consumption; 2012; Arini, N.
- ISO 20252. Market, opinion and social research-Vocabulary and service requirements, 2nd Edition; 2012
- Is „chapterisation“ a viable alternative to traditional progress indicators ?; 2012; Spicer, R., Dowling, Z.
- Internet use in households and by individual in 2012. Eurostat Statistics in Focus 50/2012; 2012; Seybert, H.
- Internet access - Households and individuals, 2012 part 2; 2012
- Internet access - Households and individuals, 2012; 2012
- Google et Médiamétrie créent une audience bimédia; 2012; Gonzales, P.
- GMI Pinnacle; 2012
- Global market research 2012; 2012
- Explaining rising nonresponse rates in cross-sectional surveys; 2012; Brick, J. M., Williams, Do.
- Eurobarometer Special surveys: Special Eurobarometer 381; 2012
- Online Surveys 2.0; 2012; Elferink, R.
- The Impact of Academic Sponsorship on Online Survey Dropout Rates; 2012; Allen, P. J., Roberts, L. D.
- Especially for You: Motivating Respondents in an Internet Panel by Offering Tailored Questions; 2012; Oudejans, M.
- Social media as a data collection tool: the impact of Facebook in behavioural research; 2012; Zoppos, E.
- Smartphone Apps and User Engagement: Collecting Data in the Digital Era; 2012; Link, M. W.
- Snowball Sampling in Online Social Networks; 2012; Raissi, M., Ackland, R.
- The Use of Facebook as a Locating and Contacting Tool; 2012; McCarthy, T.
- How Often Do You Use the App with a Bird on It? Exploring Differences in Survey Completion Times, Primacy...; 2012; Buskirk, T. D.
- Data quality of questions sensitive to social-desirability bias in web surveys; 2012; Lozar Manfreda, K., Zajc, N., Berzelak, N., Vehovar, V.
- Online Questionnaires: Development of ‘basic requirements’; 2012; Tries, S., Blanke, K.
- Social research in online context: methodological reflections on web surveys from a case study; 2012; Pandolfini, V.
- Efficacy of a health-related Facebook social network site on health-seeking behaviors; 2012; Woolley, P., Peterson, M.
- The war against unengaged online respondents; 2012; Gittelman, S. H., Trimarchi, E.
- Qualitatively Speaking: The five absolute, no-excuse must-dos for online qualitative researchers; 2012; Rossow, A.
- By the Numbers: Lessons for using online panels in B2B research; 2012; Elsner, N.
- Specialized Tools for Measuring Past Events ; 2012; Belli, R. F.
- Transparency, Access and the Credibility of Survey Research; 2012; Lupia, A.
- Can Microtargeting Improve Survey Sampling? An Assessment of Accuracy and Bias in Consumer File Marketing...; 2012; Pasek, J.
- Anonymity and Confidentiality; 2012; Tourangeau, R.
- Cognitive Evaluation of Survey Instruments: State of the Science (Art?) and Future Directions; 2012; Willis, G. B.
- Oh, Just One More Thing … Leveraging “Leave-Behinds” in Data Collection; 2012; Link, M. W.
- Paradata; 2012; Kreuter, F.
- Computation of Survey Weights: Bridging Theory and Practice; 2012; DeBell, M.
- Optimizing Response Rates; 2012; Brick, J. M.
- Modes of Data Collection; 2012; Tourangeau, R.
- The Use and Effects of Incentives in Surveys; 2012; Singer, E.
- Improving Question Design to Maximize Reliability and Validity; 2012; Krosnick, J. A.
- Respondent Attrition vs Data Attrition and Their Reduction; 2012; Olsen, R. J.
- Survey Interviewing: Deviations from the Script; 2012; Schaeffer, N. C.
- How accurate are surveys of objective phenomena?; 2012; Chang, L. C., Krosnick, J. A.
- Measure the response burden in the Swedish Intrastat system; 2012; Weideskog, F.
- Mode and non-response effects and their treatment; 2012; Chrysanthopoulos, S., Georgostathi, A.
- What can be said about quality in the Central Population Register based on a self-completion survey...; 2012; Falnes-Dalheim, E., Pedersen, H. E.
- Improving the quality of complex surveys: The case of the EU Labour Force Survey ; 2012; van der Valk, J.
- Pros and cons of Internet based User Satisfaction Surveys; 2012; Consoli, A., Matsulevits, L.
- Between demand and reality: Ensuring efficiency and quality in pretesting questionnaires; 2012; Sattelberger, S., Blanke, K.
- How to provide high data quality in online-questionnaires: Setting guidelines in design; 2012; Tries, S., Nebel, S., Blanke, K.