Web Survey Bibliography
Panels of persons who volunteer to participate in Web surveys are used to make estimates for entire populations, including persons who have no access to the Internet. One method of adjusting a volunteer sample to attempt to make it representative of a larger population involves randomly selecting a reference sample from the larger population. The act of volunteering is treated as a quasi-random process where each person has some probability of volunteering. One option for computing weights for the volunteers is to combine the reference sample and Web volunteers and estimate probabilities of being a Web volunteer via propensity modeling. There are several options for using the estimated propensities to estimate population quantities. Careful analysis to justify these methods is lacking. The goals of this article are (a) to identify the assumptions and techniques of estimation that will lead to correct inference under the quasi-random approach, (b) to explore whether methods used in practice are biased, and (c) to illustrate the performance of some estimators that use estimated propensities. Two of our main findings are (a) that estimators of means based on estimates of propensity models that do not use the weights associated with the reference sample are biased even when the probability of volunteering is correctly modeled and (b) if the probability of volunteering is associated with analysis variables collected in the volunteer survey, propensity modeling does not correct bias.
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Web survey bibliography - Sociological Methods & Research (15)
- Estimating the Impact of Measurement Differences Introduced by Efforts to Reach a Balanced Response...; 2017; Kappelhof, J. W. S.; De Leeuw, E. D.
- Taming Big Data: Using App Technology to Study Organizational Behavior on Social Media; 2015; Bail, C. A.
- The Use of a Nonprobability Internet Panel to Monitor Sexual and Reproductive Health in the General...; 2015; Legleye, S; Charrance, G.; Razafindratsima, N.; Bajos, N.; Bohet, A.; Moreau, C.
- The Impact of Mixing Modes on Reliability in Longitudinal Studies; 2014; Cernat, A.
- Panel Attrition - Separating Stayers, Fast Attriters, Gradual Attriters, and Lurkers; 2014; Lugtig, P. J.
- Asking Sensitive Questions: An Evaluation of the Randomized Response Technique Versus Direct Questioning...; 2013; Wolter, F.; Preisendoerfer, P.
- Measurement Effects of Survey Mode on the Equivalence of Attitudinal Rating Scale Questions; 2013; Klausch, L. T., Hox, J., Hox, J., Schouten, B.
- Not by the Book: Facebook as a Sampling Frame; 2012; Brickman Bhutta, C.
- Multiple Sources of Nonobservation Error in Telephone Surveys: Coverage and Nonresponse; 2011; Peytchev, A.; Carley-Baxter, L. R.; Black, M. C.
- Nonparametric Tests of Panel Conditioning and Attrition Bias in Panel Surveys; 2011; Das, M., Toepoel, V., van Soest, A.
- Introduction to the Special Issue on Web Surveys ; 2009; Witte, J. C.
- Smartphones: An Emerging Tool for Social Scientists; 2009; Raento, M., Oulasvirta, A., Eagle, N.
- Designing Scalar Questions for Web Surveys; 2009; Christian, L. M., Parsons, N. L., Dillman, D. A.
- Web-based network sampling - Efficiency and efficacy of respondent-driven sampling for online research...; 2008; Wejnert, C., Heckathorn, D. D.
- Feeling thermometers versus 7-point scales. Which are better?; 1997; Alwin, D. F.