Web Survey Bibliography
The problem with speaking about the average error of a given statistical model is that it is difficult to determine how much of the error is due to the model and how much is due to randomness. The mean square error (MSE) provides a statistic that allows for researchers to make such claims. MSE simply refers to the mean of the squared difference between the predicted parameter and the observed parameter. Formally, this can be denned as In Equation (1), E represents the expected value of the squared difference between an estimate of an unknown parameter (θ∗) and the actual observed value (θ) of the parameter. In this instance, the expected value of the MSE simply refers to the average error one would expect given the parameter estimate. MSE is often categorized as a “loss function,” meaning that it represents how wrong the estimated parameter actually is, allowing one Substantively, ...
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Web survey bibliography (4086)
- Survey Methodology (Wiley Series in Survey Methodology); 2009; Groves, R. M., Fowler, F. J., Couper, M. P., Lepkowski, J. M., Singer, E., Tourangeau, R.
- Foundations of Quality Project Overview to Support RFPs; 2008; Tom Evans; Efrain Ribeiro; Renee Smith
- Crowdsourcing user studies with Mechanical Turk; 2008; Kittur, A., Chi, E. H., Suh, Bo.
- Mean Square Error (MSE); 2008; Dietrich, B.J.
- Maximizing respondent engagement through survey design; 2008; Strube, S. N., Zdanowicz, Y.
- Platforms for data quality progress: The client's guide to rapid improvement of online research; 2008
- Online Focus Groups; 2008; Gaiser, T. J.
- ISO 9001:2008 Quality management systems -- Requirements; 2008
- Designing a Web-Based Survey Tool for small businesses and non-profit organizations; 2008; Zhang, D.
- Is the digital divide still closing? New evidence points to skewed online results absent non-Internet...; 2008; Callegaro, M., Wells, T.
- Survey response rate levels and trends in organizational research; 2008; Baruch, Y., Holtom, B. C.
- Social desirability bias in CATI, IVR and Web surveys: The effects of mode and question sensitivity; 2008; Kreuter, F., Presser, S., Tourangeau, R.
- Introducing Visual Methods ; 2008; Prosser, J., Loxley, A.
- The semantic differential technique; 2008; Stoutenborough, J. W.
- The advisory panel on online public opinion survey quality - Final report June 4, 2008; 2008
- Testing survey questions; 2008; Campanelli, P.
- Telephone survey methodology: Adapting to change; 2008; Tucker, C., Lepkowski, J. M.
- Some consequences of survey mode changes in longitudinal surveys; 2008; Dillman, D. A.
- Sample factors that influence data quality; 2008; Gailey, R., Teal, D., Haechrel, E.
- Representativity of web surveys – an illusion?; 2008; Bethlehem, J.
- Recruitment and retention for a consumer panel; 2008; Tortora, R. D.
- Probabilistic methods in surveys and offical statistics; 2008; Vehovar, V., Zaletel, M., Seljak, R.
- Privacy, confidentiality, and response burden as factors in telephone survey nonresponse; 2008; Singer, E., Presser, S.
- Personal data of 600,000 on lost laptop; 2008; Evans, Mi.
- Online panel management practices that minimize satisficing behavior; 2008; Weber, S.
- Modeling campaign dynamics on the web in the 2008 National Annenberg Election Study; 2008; Johnston, R.
- Mode effects; 2008; Jans, M.
- Mobile web surveys: A preliminary discussion of methodological implications; 2008; Fuchs, M.
- Missing data; 2008; de Leeuw, E. D., Hox, J.
- Measuring customer satisfaction and loyalty, Third Edition: Survey design, use, and statistical analysis...; 2008; Hayes, B. E.
- IVR: Interactive voice technology; 2008; Miller-Steiger, D., Conroy, B.
- Internet surveys and national election studies: A Symposium; 2008; Clarke, H. D., Sanders, D., Stewart, M. C., Whiteley, P.
- Internet surveys; 2008; Lozar Manfreda, K., Vehovar, V.
- History of the browser user agent string; 2008; Andersen, A.
- Heuristics and biases as measures of critical thinking: Associations with cognitive ability and thinking...; 2008; West, R. F., Toplak, M. E., Stanovich, K. E.
- Foundation of quality project overview; 2008
- Email survey; 2008; Porter, S. R.
- Effects of using a grid versus a sequential form of the ACS basic demographic data; 2008; Chesnut, J.
- Designing online election surveys: Lessons from the 2004 Australian election; 2008; Gibson, R., McAllister, I.
- College sophomores in the laboratory redux: Influences of a narrow data base on social psychology'...; 2008; Henry, P. J.
- Mixed Modes and Measurement Error: Study design and literature review; 2008; Hope, S., Nicolaas, G.
- 26 questions to help research buyers of online samples; 2008
- Forms that Work - Designing Web Forms for Usability; 2008; Jarrett, C., Gaffney, G.
- Whose Space? Differences Among Users and Non-Users of Social Network Sites; 2008; Hargittai, E.
- ‘Looking at’, ‘Looking up’ or ‘Keeping up with’ People? Motives...; 2008; Joinson, A. N.
- Design Variations in Adaptive Web Sampling; 2008; Vincent, K. S.
- Objectivity, Reliability, and Validity of Search Engine Count Estimates ; 2008; Janetzko, D.
- TitleInternet-basierte Messung sozialer Erwünschtheit: Theoretische Grundlagen und experimentelle Untersuchung...; 2008; Kaufmann, E., Reips, U.-D.
- Sozialforschung im Internet: Methodologie und Praxis der Online-Befragung; 2008; Jackob, N., Schoen, H., Zerback, T. (eds.)
- An online panel as a platform for multi-disciplinary research; 2008; Scherpenzeel, A.