Web Survey Bibliography
Non-response bias can significantly compromise the representativeness of a sample. In order to combat these problems, researchers tend to mandate marginal quotas to known population proportions. However, the problems associated with quota sampling have been extensively documented when marginal quotas do not fill up at the same time. Differential sampling, whether through propensity scores or model-based response rate adjustments, avoids the problems involved in quota sampling. Differential sampling oversamples subpopulations with lower response rates to ensure survey respondents are balanced according to population proportions. Adjusting for these subpopulations becomes even more important in the online space where individual response rates vary dramatically.
Practitioners who use online panels must develop solutions for coverage limitations, conditioning and respondent attrition, source variability, and non-response bias. We discuss how to more effectively correct non-response bias in online sample to create more accurate estimators from data collected online. The most common way to adjust for non-response bias involves modeling the response rate for each of the subpopulations and oversampling accordingly. Some real time sources use aggregate level demographic estimates to adjust the flow of respondents into their surveys. However, demographics do not account for a large percentage of the variation in response rates. Panel companies can instead use historical response rate data at the individual level to accurately adjust the flow of respondents and correct for non-response. We discuss a system of implementing individual-level response rate estimation and show the advantages when compared to model-based response rate estimates.
Conference Homepage (abstract)
Web survey bibliography (457)
- Handbook of Research Methods in Health Social Sciences; 2017; Liamputtong, P.
- Necessary but Insufficient: Why Measurement Invariance Tests Need Online Probing as a Complementary...; 2017; Meitinger, K.
- Device and Internet Use among Spanish-dominant Hispanics: Implications for Web Survey Design and Testing...; 2017; Trejo, Y. A. G.; Schoua-Glusberg, A.
- Role of online survey tools in creating temporally accurate Environmental Product Declarations (EPD)...; 2017; Ganguly, I.; Bowers, T.; Pierobon, F.; Eastin, I.
- CAQDAS at a Crossroads: Affordances of Technology in an Online Environment; 2017; Silver, C.; Bulloch, L. S.
- Development and Pilot Test of a Mobile Application for Field Data Collection; 2016; Chiappetta, L.; Kerr, M. M.
- A streamlined approach to online linguistic surveys; 2016; Erlewine, M. Y.; Kotek, H.
- The Effects of Vignette Placement on Attitudes Toward Supporting Family Members; 2016; Lau, C. Q., Seltzer, J. A., Bianchi, S. M.
- Using Web Panels to Quantify the Qualitative: The National Center for Health Statistics Research and...; 2016; Scanlon, P. J.
- Bees to Honey or Flies to Manure? How the Usual Subject Recruitment Exacerbates the Shortcomings of...; 2016; Snell, S. A., Hillygus, D. S.
- 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.
- GreenBook Research Industry Trends Report; 2015; Murphy, L. (Ed.)
- Does Sequence Matter in Multimode Surveys: Results from an Experiment; 2014; Wagner, J., Arrieta, J., Guyer, H., Ofstedal, M. B.
- The Use of Cognitive Interviewing Methods to Evaluate Mode Effects in Survey Questions; 2014; Gray, M., Blake, M., Campanelli, P.
- Build your own social network laboratory with Social Lab: a tool for research in social media; 2014; Garaizar, P., Reips, U.-D.
- Using Eye Tracking to Evaluate Email Notifications of Surveys and Online Surveys Collecting Address...; 2014; Olmsted, E. L., Nichols, E. M.
- Correlates of Attrition in the German Internet Panel: Drop-Outs and Sleepers; 2014; Blom, A. G., Beissel-Durrant, G.
- Survey Breakoff in Online Panels; 2014; McCutcheon, A. L.
- Inside the Turk Understanding Mechanical Turk as a Participant Pool; 2014; Paolacci, G., Chandler, J.
- Nonresponse and measurement error in an online panel; 2014; Roberts, C., Allum, N., Sturgis, P.
- Estimating the effects of nonresponses in online panels through imputation; 2014; Zhang, W.
- Professional respondents in nonprobability online panels; 2014; Hillygus, D. S., Jackson, N. M., Young, M.
- Informing panel members about study results; 2014; Scherpenzeel, A., Toepoel, V.
- Determinants of the starting rate and the completion rate in online panel studies; 2014; Goeritz, A.
- The untold story of multi-mode (online and mail) consumer panels; 2014; McCutcheon, A. L., Rao, K., Kaminska, O.
- Online panels and validity; 2014; Groenlund, K., Strandberg, K.
- Assessing representativeness of a probability-based online panel in Germany; 2014; Struminskaya, B., Kaczmirek, L., Schaurer, I., Bandilla, W.
- 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.
- Motives for joining nonprobability online panels and their association with survey participation behavior...; 2014; Keusch, F., Batinic, B., Mayerhofer, W.
- Targeting the bias – the impact of mass media attention on sample composition and representativeness...; 2014; Steinmetz, S., Oez, F., Tijdens, K. G.
- Exploring selection biases for developing countries - is the web a promising tool for data collection...; 2014; Tijdens, K. G., Steinmetz, S.
- The quality of ego-centered social network data in web surveys: experiments with a visual elicitation...; 2014; Marcin, B., Matzat, U., Snijders, C.
- Switching the polarity of answer options within the questionnaire and using various numbering schemes...; 2014; Struminskaya, B., Schaurer, I., Bosnjak, M.
- Measuring the very long, fuzzy tail in the occupational distribution in web-surveys; 2014; Tijdens, K. G.
- Interest Bias – An Extreme Form of Self-Selection?; 2014; Cape, P. J., Reichert, K.
- Online Qualitative Research – Personality Matters ; 2014; Tress, F., Doessel, C.
- Recent Books and Journals in Public Opinion, Survey Methods, and Survey Statistics; 2014; Callegaro, M.
- Does Gamification Work? - A Literature Review of Empirical Studies on Gamification ; 2014; Hamari, J., Koivisto, J., Sarsa, H.
- The Use of Paradata to Predict Future Cooperation in a Panel Study; 2014; Funke, F., Goeritz, A.
- Pret met panels [Fun online]; 2013; Roberts, A., de Leeuw, E. D., Hox, J., Klausch, L. T., de Jongh, A.
- The Short-term Campaign Panel of the German Longitudinal Election Study 2009. Design, Implementation...; 2013; Steinbrecher, M., Rossmann, J.
- The Future of Social Media, Sociality, and Survey Research; 2013; Hill, C., Dever, J. A.
- Second Life as a Survey Lab: Exploring the Randomized Response Technique in a Virtual Setting; 2013; Richards, A., Dean, E.
- Virtual Cognitive Interviewing Using Skype and Second Life; 2013; Dean, E., Head, B., Swicegood, J. E.
- Social Media, Sociality, and Survey Research; 2013; Hill, C., Dean, E., Murphy, J.
- Investigation of background acoustical effect on online surveys: A case study of a farmers' market...; 2013; Tang, Xi.
- Should the third reminder be sent? The role of survey response timing on web survey results; 2013; Rao, K., Pennington, J.
- Web panel surveys – can they be designed and used in a scientifically sound way?; 2013; Svensson, J.
- Using an Item Response Theory Approach to Measure Survey Mode of Administration Effects: Analysis of...; 2013; Mariano, L. T., Elliott, M. N.