Web Survey Bibliography
All social surveys suffer from different types of errors, of which one of the most studied is non-response bias. Non-response bias is a systematic error that occurs because individuals differ in their accessibility and propensity to participate in a survey according to their own characteristics as well as those from the survey itself. The extent of the problem heavily depends on the correlation between response mechanisms and key survey variables. However, non-response bias is difficult to measure or to correct for due to the lack of relevant data about the whole target population or sample. In this paper, non-response follow-up surveys are considered as a possible source of information about non-respondents. Non-response follow-ups, however, suffer from two methodological issues: they themselves operate through a response mechanism that can cause potential non-response bias, and they pose a problem of comparability of measure, mostly because the survey design differs between main survey and non-response follow-up. In order to detect possible bias, the survey variables included in non-response surveys have to be related to the mechanism of participation, but not be sensitive to measurement effects due to the different designs. Based on accumulated experience of four similar non-response follow-ups, we studied the survey variables that fulfill these conditions. We differentiated socio-demographic variables that are measurement-invariant but have a lower correlation with non-response and variables that measure attitudes, such as trust, social participation, or integration in the public sphere, which are more sensitive to measurement effects but potentially more appropriate to account for the non-response mechanism. Our results show that education level, work status, and living alone, as well as political interest, satisfaction with democracy, and trust in institutions are pertinent variables to include in non-response follow-ups of general social surveys.
All social surveys suffer from different types of errors, of which one of the most studied is non-response bias. Non-response bias is a systematic error that occurs because individuals differ in their accessibility and propensity to participate in a survey according to their own characteristics as well as those from the survey itself. The extent of the problem heavily depends on the correlation between response mechanisms and key survey variables. However, non-response bias is difficult to measure or to correct for due to the lack of relevant data about the whole target population or sample. In this paper, non-response follow-up surveys are considered as a possible source of information about non-respondents. Non-response follow-ups, however, suffer from two methodological issues: they themselves operate through a response mechanism that can cause potential non-response bias, and they pose a problem of comparability of measure, mostly because the survey design differs between main survey and non-response follow-up. In order to detect possible bias, the survey variables included in non-response surveys have to be related to the mechanism of participation, but not be sensitive to measurement effects due to the different designs. Based on accumulated experience of four similar non-response follow-ups, we studied the survey variables that fulfill these conditions. We differentiated socio-demographic variables that are measurement-invariant but have a lower correlation with non-response and variables that measure attitudes, such as trust, social participation, or integration in the public sphere, which are more sensitive to measurement effects but potentially more appropriate to account for the non-response mechanism. Our results show that education level, work status, and living alone, as well as political interest, satisfaction with democracy, and trust in institutions are pertinent variables to include in non-response follow-ups of general social surveys. - See more at: https://ojs.ub.uni-konstanz.de/srm/article/view/6138#sthash.CEiOvCVB.dpuf
Web survey bibliography (109)
- Telephone versus Online Survey Modes for Election Studies: Comparing Canadian Public Opinion and Vote...; 2017; Breton, C.; Cutler, F.; Lachance, S.; Mierke-Zatwarnicki, A.
- Comparing acquiescent and extreme response styles in face-to-face and web surveys; 2017; Liu, M.; Conrad, F. G.; Lee, S.
- The Failure of the Polls: Lessons Learned from the 2015 UK Polling Disaster; 2017; Sturgis, P.
- Incorporating eye tracking into cognitive interviewing to pretest survey questions; 2016; Neuert, C.; Lenzner, T.
- Are interviews costing £0.08 a waste of money? Reviewing Google Surveys for Wisdom of the Crowd...; 2016; Roughton, G.; MacKay, I.
- The Effects of a Delayed Incentive on Response Rates, Response Mode, Data Quality, and Sample Bias in...; 2016; McGonagle, K., Freedman, V. A.
- Privacy Concerns in Responses to Sensitive Questions. A Survey Experiment on the Influence of Numeric...; 2016; Bader, F., Bauer, J., Kroher, M., Riordan, P.
- Does survey mode matter for studying electoral behaviour? Evidence from the 2009 German Longitudinal...; 2016; Bytzek, E.; Bieber, I. E.
- Forecasting proportional representation elections from non-representative expectation surveys; 2016; Graefe, A.
- Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk; 2016; Berinsky, A.; Huber, G. A.; Lenz, G. S.
- 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...
- Sample Representation and Substantive Outcomes Using Web With and Without Incentives Compared to Telephone...; 2016; Lipps, O.; Pekari, N.
- Evaluating a New Proposal for Detecting Data Falsification in Surveys; 2016; Simmons, K.; Mercer, A. W.; Schwarzer, S.; Courtney, K.
- Identifying Pertinent Variables for Nonresponse Follow-Up Surveys. Lessons Learned from 4 Cases in Switzerland...; 2016; Vandenplas, C.; Joye, D.; Staehli, M. E.; Pollien, A.
- Methods can matter: Where Web surveys produce different results than phone interviews; 2016; Keeter, S.
- HUFFPOLLSTER: Why Reaching Latinos Is A Challenge For Pollsters; 2016; Jackson, N. M.; Edwards-Levy, A.; Velencia, J.
- Moderators of Candidate Name-Order Effects in Elections: An Experiment; 2016; Kim, Nu.; Krosnick, J. A.; Casasanto, D.
- Measuring Generalized Trust: An Examination of Question Wording and the Number of Scale Points; 2016; Lundmark, S.; Giljam, M.; Dahlberg, S.
- Online and Social Media Data As an Imperfect Continuous Panel Survey; 2016; Diaz, F.; Garmon, F.; Hofman, J. K.; Kiciman, E.; Rothschild, D.
- Translating Answers to Open-ended Survey Questions in Cross-cultural Research: A Case Study on the Interplay...; 2015; Behr, D.
- Using Video to Reinvigorate the Open Question; 2015; Cape, P.
- On Bias Adjustments for Web Surveys; 2015; Fan, L.; Lou, W.; Landsman, V.
- Measuring Political Knowledge in Web-Based Surveys: An Experimental Validation of Visual Versus Verbal...; 2015; Munzert, S.; Selb, P.
- Mode System Effects in an Online Panel Study: Comparing a Probability-based Online Panel with two Face...; 2015; Struminskaya, B.; De Leeuw, E. D.; Kaczmirek, L.
- Data collection mode effect on feeling thermometer questions: A comparison of face-to-face and Web surveys...; 2015; Liu, M., Wang, Yi.
- Do Attempts to Improve Respondent Attention Increase Social Desirability Bias?; 2015; Clifford, S.; Jerit, J.
- HUFFPOLLSTER: Pollsters Debate If Modern Surveys Can Be Trusted; 2015; Blumenthal, M.; Edwards-Levy, A.; Velencia, J.
- Can a non-probabilistic online panel achieve question quality similar to that of the European Social...; 2015; Revilla, M.; Saris, W. E.; Loewe, G.; Ochoa, C.
- Data Collection Mode Effects On Political Knowledge; 2014; Liu, M., Wang, Y.
- Self-reported cheating in web surveys on political knowledge; 2014; Jensen, C., Thomsen, J. P. F.
- The Power of Partisanship in Brazil: Evidence from Survey Experiments; 2014; Samuels, D., Zucco, C.
- Online Polls and Registration-Based Sampling: A New Method for Pre-Election Polling; 2014; Barber, M. J., Mann, C. B., Monson, J. Q., Patterson, K. D.
- Does Survey Mode Still Matter? Findings from a 2010 Multi-Mode Comparison; 2014; Ansolabehere, S., Schaffner, B. F.
- Measuring Political Participation—Testing Social Desirability Bias in a Web-Survey Experiment; 2014; Persson, M., Solevid, M.
- What Does the Satisfaction with Democracy Measure Mean to Respondents in Different Countries? How Cross...; 2014; Behr, D., Braun, M.
- Professional respondents in nonprobability online panels; 2014; Hillygus, D. S., Jackson, N. M., Young, M.
- Online panels and validity; 2014; Groenlund, K., Strandberg, K.
- Two Are Better Than One: The Use of a Mixed-Mode Data Collection to Improve the Electoral Forecast; 2014; de Rada, V. D., Pasadas del Amo, S.
- The Short-term Campaign Panel of the German Longitudinal Election Study 2009. Design, Implementation...; 2013; Steinbrecher, M., Rossmann, J.
- Relative Mode Effects on Data Quality in Mixed-Mode Surveys by an Instrumental Variable; 2013; Vannieuwenhuyze, J. T. A., Revilla, M.
- Web Versus Outbound: A Mode Face-Off Following the Presidential Debate; 2013; Marlar, J.
- Propensity Score Weighting – Can Personality Adjust for Selectivity?; 2013; Glantz, A., Greszki, R.
- Especially for You: Motivating Respondents in an Internet Panel by Offering Tailored Questions; 2012; Oudejans, M.
- Presidential Elections in Iceland 2012 – Did online panel surveys give false hope to new candidates...; 2012; Jonsdottir, G. A., Dofradottir, A. G., Bjornsdottir, A. E.
- Effects of Technical Difficulties on Item Nonresponse and Response Favorability in a Mixed-Mode Survey...; 2012; Gibson, J. L.
- Where is Neutral? Using Negativity Biases to Interpret Thermometer Scores; 2012; Soroka, S., Albaugh, Q.
- I Got a Feeling: Comparison of Feeling Thermometers with Verbally Labeled Scales in Attitude Measurement...; 2012; Thomas, R. K., Bremer, J.
- Scrutinizing Dynamics – Rolling panel waves in theory and practice; 2012; Faas, T., Blumenberg, J. N.
- Toward wiser public judgment; 2011; Yankelovich, D., Friedman, W.
- Mass informed consent: Evidence on upgrading democracy with polls and new media; 2011; Simon, A. F.