Web Survey Bibliography
There is widespread consensus that using survey weights is necessary for descriptive inference (i.e., percentages, means) if the findings are to be generalized to the population from which the sample was drawn. There is less agreement on when and whether weights should be used with multivariate methods, such as linear or logistic regression analysis (Winship & Radbill, 1994; Gelman, 2007). If the sample selection and nonresponse are nonignorable, it is necessary to incorporate survey design features into the estimation of linear regression coefficients (Kott, 2007). Weighted regression, however, can produce inefficient standard errors of the estimates. Rather than use weighted regression, one alternative is to use a model-based approach that includes variables in a regression model that reflect sample design features (Gelman, 2007). In this paper, we use a series of simulation models based on the 2005 Current Population Survey to explore how sensitive a model-based strategy is to misspecification. A practical concern of a model-based strategy is that it requires an analyst to replicate many of the tasks of a survey statistician; when done incorrectly or with incomplete information, a model-based strategy could be risky. Our results show that, under some circumstances, the smaller standard errors from a model-based strategy may come at the cost of biased b-coefficients, so an unweighted approach should be used cautiously.
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Web survey bibliography (183)
- Using experts’ consensus (the Delphi method) to evaluate weighting techniques in web surveys not...; 2017; Toepoel, V.; Emerson, H.
- A Partially Successful Attempt to Integrate a Web-Recruited Cohort into an Address-Based Sample; 2017; Kott, P. S., Farrelly, M., Kamyab, K.
- Overview: Online Surveys; 2017; Vehovar, V.; Lozar Manfreda, K.
- Inferences from Internet Panel Studies and Comparisons with Probability Samples; 2016; Lachan, R.; Boyle, J.; Harding, R.
- Integration of a phone-based household travel survey and a web-based student travel survey; 2016; Verreault, H.; Morency, C.
- Estimation and Adjustment of Self-Selection Bias in Volunteer Panel Web Surveys ; 2016; Niu, Ch.
- Calculating Standard Errors for Nonprobability Samples when Matching to Probability Samples ; 2016; Lee, Ad.; ZuWallack, R. S.
- Establishing the accuracy of online panels for survey research; 2016; Bruggen, E.; van den Brakel, J.; Krosnick, J. A.
- Evaluating Three Approaches to Statistically Adjust for Mode Effects; 2016; Kolenikov, S.; Kennedy, C.
- Linearization Variance Estimators for Mixed ‒ mode Survey Data when Response Indicators are Modeled...; 2016; Demnati, A.
- Options for Fielding and Analyzing Web Surveys; 2016; Schonlau, M.; Couper, M. P.
- Report of the Inquiry into the 2015 British general election opinion polls; 2016; Sturgis, P., Baker, N., Callegaro, M., Fisher, St., Green, J., Jennings, W., Kuha, J., Lauderdale, B...
- Solving the Nonresponse Problem With Sample Matching?; 2016
- Online and Social Media Data As an Imperfect Continuous Panel Survey; 2016; Diaz, F.; Garmon, F.; Hofman, J. K.; Kiciman, E.; Rothschild, D.
- Quota Controls in Survey Research.; 2016; Gittelman, S. H.; Thomas, R. K.; Lavrakas, P. J.; Lange, V.
- Scientific Surveys Based on Incomplete Sampling Frames and High Rates of Nonresponse; 2016; Fahimi, M.; Barlas, F. M.; Thomas, R. K.; Buttermore, N. R.
- Doing Surveys Online ; 2016; Toepoel, V.
- Using Mobile Phones for High-Frequency Data Collection; 2015; Azevedo, J. P.; Ballivian, A.; Durbin, W.
- On Bias Adjustments for Web Surveys; 2015; Fan, L.; Lou, W.; Landsman, V.
- The quality of data collected using online panels: a decade of research ; 2015; Callegaro, M.
- Does the use of mobile devices (tablets and smartphones) affect survey quality and choice behaviour...; 2015; Liebe, U., Glenk, K., Oehlmann, M., Meyerhoff, J.
- Web-based survey, calibration, and economic impact assessment of spending in nature based recreation; 2015; Paudel, K. P., Devkota, N., Gyawali, B.
- Using Web Panels for Official Statistics; 2014; Bethlehem, J.
- Self-reported cheating in web surveys on political knowledge; 2014; Jensen, C., Thomsen, J. P. F.
- Keeping Surveys Valid, Reliable, and Useful: A Tutorial; 2014; Greenberg, M. R., Weiner, M. D.
- Prioritisation of alternatives with analytical hierarchy process plus response latency and web survey...; 2014; Barone, S. Errore, A., Lombardo, A.
- 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.
- Using Paradata to Predict and to Correct for Panel Attrition in a Web-based Panel Survey; 2014; Rossmann, J., Gummer, T.
- Improving cheater detection in web-based randomized response using client-side paradata; 2014; Dombrowski, K., Becker, C.
- Modelling ”don’t know” responses in rating scales; 2014; Manisera, M., Zuccolotto, P.
- User Modeling via Machine Learning and Rule-Based Reasoning to Understand and Predict Errors in Survey...; 2013; Stuart, L. C.
- Comparison of Three Modes for a Crime Victimization Survey; 2013; Laaksonen, S., Heiskanen, M.
- The Short-term Campaign Panel of the German Longitudinal Election Study 2009. Design, Implementation...; 2013; Steinbrecher, M., Rossmann, J.
- Too Fast, Too Straight, Too Weird: Post Hoc Identification of Meaningless Data in Internet ; 2013; Leiner, D. J.
- Assessing Nonresponse Bias in the Green Technologies and Practices Survey; 2013; Meekins, B., Sverchkov, M., Stang, S.
- Web Panel Representativeness; 2013; Bianchi, A., Biffignandi, S.
- On the Impact of Response Patterns on Survey Estimates from Access Panels; 2013; Enderle, T., Muennich, R., Bruch, C.
- Unit Nonresponse and Weighting Adjustments: A Critical Review; 2013; Brick, J. M.
- Adjusting for bias in a mixed-mode CAWI survey on University students ; 2013; Clerici, R., Giraldo, A.
- A probability-based web panel for the UK: What could it look like?; 2013; Nicolaas, G.
- Panel Attrition: Separating Stayers, Sleepers and Other Types of Drop-Out in an Internet Panel; 2013; Lugtig, P. J.
- Speeding and Non-Differentiation in Web Surveys: Evidence of Correlation and Strategies for Reduction...; 2013; Zhang, Che.
- Web Versus Outbound: A Mode Face-Off Following the Presidential Debate; 2013; Marlar, J.
- The Effects of Errors in Paradata on Weighting Class Adjustments: A Simulation Study; 2013; West, B. T.
- Practical tools for designing and weighting survey samples; 2013; Valliant, R. L., Daver, J. A., Kreuter, F.
- Moving an established survey online – or not?; 2013; Barber, T., Chilvers, D., Kaul, S.
- Measuring working conditions in a volunteer web survey; 2013; de Pedraza, P., Villacampa, A.
- Propensity Score Weighting – Can Personality Adjust for Selectivity?; 2013; Glantz, A., Greszki, R.
- Eurobarometer Special surveys: Special Eurobarometer 381; 2012