Web Survey Bibliography
Many internet-panels consist of self-selected respondents and hence cover a relatively small part of the population. Estimates based on Internet-panels therefore may suffer from non-coverage and self-selection bias. One way to correct for these biases is to use adjustment weighting(Lee, 2006). However, when Internet-panel respondents are intrinsically different from the general population, previous studies showed that weighting may result in an increase in bias (for example, see Loosveldt and Sonck, 2008).
How can we show that panel-members are intrinsically different from respondents that take part in a conventional random-sample survey? To answer this question we compared the results of a volunteer Internet-panel to the results of a web-interview (WI) based on a random sample of the same population. First, differences in population coverage are studied. Secondly, we test if significant differences in coverage predict differences on dependent variables. Finally, we use propensity matching to test for self-selection bias. This contribution sheds light on the extent of coverage bias relative to self-selection bias in random- and volunteer opt-in Internet surveys.
We use propensity score matching to answer our question. Propensity scores summarize the conditional probability of a respondent to be member of either the random or volunteer sample based on a set of covariates. When the propensity score includes relevant covariates, respondents with the same propensity scores can be matched. Remaining differences between dependent variables after matching cannot be caused by coverage errors, and are indicative for the size of self-selection bias.
Journal Homepage (abstract)/(full text)
Web Survey Bibliography (495)
- Web panel surveys – can they be designed and used in a scientifically sound way?; 2013; Svensson , J.
- A standard with quality indicators for web panel surveys: a Swedish example; 2013; Nyfjaell, M.
- Web Panels for Official Statistics? ; 2013; Bethlehem, J., Cobben, F.
- Using Internet Panel Surveys for Behavioral Health Surveillance; 2013; Gotway Crawford, C., Okoro, C. A., Dhingra, S., Akcin, H., Zhao, G., Ford, D., Pierannunzi, C.
- Lotteries and study results in market research online panels; 2013; Goeritz, A.; Luthe, S. C.
- Leveraging mobile and online qualitative to get inside shoppers’ heads; 2013; Bryson, J., Ritzo, J.
- 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.
- Going online with a face-to-face household panel: initial results from an experiment on the Understanding...; 2013; Jaeckle, A., Lynn, P., Burton, J.
- Targeted response inducement strategies on longitudinal surveys; 2013; Lynn, P.
- Best of Both Worlds? Can we make convenience samples representative?; 2013; Doe, P.
- Evaluating the left‐right dimension: Category Selection Probing conducted in an online access...; 2013; Huefken , V.
- Random versus Systematic Error in a Mixed Mode Online-Telephone Survey; 2013; Hox, J., Scherpenzeel, A., Boeve, A., Boeve, A., de Leeuw, E. D.
- Online Survey Participation via Mobile Devices: implications for nonresponse; 2013; Poggio, T., Bosnjak, M.
- Mobility and Smartphones: a pilot study of travel data collection among experienced and inexperienced...; 2013; Douhou, S., Scherpenzeel, A.
- Mobile devices a way to recruit hard-to-reach groups? Results from a pilot study comparing desk top...; 2013; Toepoel, V., Lugtig, P. J.
- Identifying and Mitigating Satisficing in Web Surveys: Some Experimental Evidence; 2013; Rossmann, J.
- Latent legitimacy: joint effects of religious orientation on the association between values and acceptance...; 2013; Henseler, A. K., Siegers, P., Beckers, T.
- Identifying Satisficing Respondents in Web Surveys: A Comparison of Different Response Time-Based Approaches...; 2013; Rossmann, J.
- Does It Pay Off to Include Non-Internet Households in an Internet Panel? ; 2013; Leenheer, J., Scherpenzeel, A.
- A probability-based web panel for UK policy research: some initial thoughts from a Government survey...; 2013; Littlechild, J.
- Factors Influencing Survey Participation Rates on an Online, Probability-Based Research Panel; 2013; Wiest, D.
- Will Snowball Sampling Leave Your Data in the Cold?; 2013; Cavallaro, K.
- Panel Attrition: Separating Stayers, Sleepers and Other Types of Drop-Out in an Internet Panel; 2013; Lugtig, P. J.
- Innovative Retention Methods in Panel Research: Can SmartPhones Improve Long-Term Panel Participation...; 2013; Dayton, J. J., Dyer, A.
- Predicting Survey Breakoff in Internet Survey Panels; 2013; Al Baghal, T., McCutcheon, A. L., Tsabutashvili, D.
- Online Panels: Recruitment Based on “Hot Topics” – What are the Consequences?; 2013; Andreasson, M., Martinsson, J.
- Responsive Design for Web Panel Data Collection; 2013; Bianchi, A., Biffignandi, S.
- Effects of Lotteries on Response Behavior in Online Panels; 2013; Goeritz, A., Luthe, S. C.
- Lotteries and study results in market research online panels; 2013; Goeritz, A., Luthe, S. C.
- Ten questions to ask your online survey provider; 2013; Williams, D.
- An approach to selecting online respondents; 2013; Terhanian, G.
- By the Numbers: Theory of adaptation or survival of the fittest?; 2013; Cavallaro, K.
- Using a web-based survey tool to undertake a Delphi study: Application for nurse education research; 2013; Gill, F. J., Leslie, G. D., Grech, C., Latour, J. M.
- Does one really know?: Avoiding noninformative answers in a reliable way.; 2013; de Leeuw, E. D., Boevee, A., Hox, J.
- Sensitive Topics in PC and Mobile Web Surveys; 2013; Mavletova, A. M., Couper, M. P.
- Sampling online communities: using triplets as basis for a (semi-) automated hyperlink web crawler.; 2013; Veny, Y.
- Propensity Score Weighting – Can Personality Adjust for Selectivity?; 2013; Glantz, A., Greszki, R.
- GESIS Online Panel Pilot: Results from a Probability-Based Online Access Panel; 2013; Kaczmirek, L., Bandilla, W., Schaurer, I., Struminskaya, B., Weyandt, K.
- Innovation in Data Collection: the Responsive Design Approach; 2013; Bianchi, A., Biffignandi, S.
- Break-off and attrition in the GIP amongst technologically experienced and inexperienced participants...; 2013; Blom, A. G., Bossert, D., Clark, V., Funke, F., Gebhard, F., Holthausen, A., Krieger, U., Wachenfeld...
- Nonresponse and Nonresponse Bias in a Probability-Based Internet Panel; 2013; Blom, A. G., Bossert, D., Funke, F., Gebhard, F., Holthausen, A., Krieger, U.
- Rewards - Money for Nothing?; 2013; Cape, P. J., Martin, P.
- Effects of incentive reduction after a series of higher incentive waves in a probability-based online...; 2013; Struminskaya, B., Kaczmirek, L., Schaurer, I., Bandilla, W.
- Timing of Nonparticipation in an Online Panel: The effect of incentive strategies; 2013; Douhou, S., Scherpenzeel, A.
- Measurement effects in mixed-mode panel surveys; 2013; Lugtig, P. J.
- Experiences from a probability-based Internet panel: Sample, recruitment and participation; 2013; Scherpenzeel, A.
- Participation and engagement in web surveys of the general population: An overview of challenges and...; 2013; Roberts, C.
- How Do Lotteries and Study Results Influence Response Behavior in Online Panels?; 2013; Goeritz, A., Luthe, S. C.
- Sample composition discrepancies in different stages of a probability-based online panel; 2013; Bosnjak, M., Haas, I., Galesic, M., Kaczmirek, L., Bandilla, W., Couper, M. P.