Web Survey Bibliography
A core tenet of survey research is that the inferences one makes about the population can only be as good as the quality of the respondents in the sample. However, with declines in probability sample response rates and increases in non-probability Internet-based research, researchers have found it increasingly difficult to agree on the quality of a survey sample. Contributing to this difficulty is the variety of research studies that have evaluated the quality of survey data derived from probability-based and non-probability-based sources and the effectiveness of statistical methods to reduce error in data from
these sources. Specifically, some research has documented a greater average error among non-probability samples relative to probability samples (Chang & Krosnick, 2009; Yeager et al., in press), while other research has found few or small differences between the two. Other research has pointed to greater variability in results from surveys non-probability samples of Internet volunteers. For instance, Dedeker (2006) conducted the same study twice on the same Internet survey panel and reached two different business conclusions. An additional study found five to ten times greater variability in error among a sample of seven Internet surveys of non-probability samples versus seven probability sample surveys (Yeager et al., in press). Similarly-sized variability was found in the National Dutch Online Panel Comparison Study. Relatedly, statistical methods such as post-stratification survey weighting have inconsistent effects on non-probability sample surveys, and in some cases increase survey error. It is critically important to synthesize the survey accuracy studies summarized above as well as others. The present study will evaluate the evidence from more than 45 different studies have assessed the accuracy of non-probability sample surveys and the effectiveness of methods to improve their accuracy,
with the aim of helping researchers and consumers to have more informed expectations about data quality in their surveys.
Conference Homepage (abstract)
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.