Web Survey Bibliography
Relevance and research question: Nonserious answering is one of the most important threats to the validity of online research (Oppenheimer, 2009). Respondents with little motivation to participate, or respondents who are interested in a survey's content or methodology only may decide to participate without giving serious answers, thus increasing noise and reducing experimental power.
Methods and data: One approach to identifying nonserious participants is to directly ask respondents about the seriousness of their participation (Klauer, Musch & Naumer, 2000; Musch & Klauer, 2002; Reips, 2000, 2002). We hypothesized that when given an opportunity to do so, randomly answering participants might be willing to identify themselves to help researchers (Reips, 2009). To validate this approach, we questioned a sample of more than 3000 respondents in the week prior to the German 2009 federal election to the Bundestag. We asked the participants whether they were responding to the questions in earnest, expecting that the exclusion of nonserious participants would help to improve data quality.
Results: We found that restricting analyses to serious participants allowed a more valid forecast of the election result. Moreover, serious participants answered attitudinal questions in a more consistent manner than nonserious participants. For example, among serious participants, self-ratings on a left-right scale correlated more strongly with approval ratings for the two major parties (CDU/CSU and SPD), and intentions to vote corresponded better with the participant’s recollections of their voting behavior in a previous election.
Added value: Taken together, our results document the usefulness of employing seriousness checks to improve data validity. We therefore recommend to routinely employ seriousness checks in online surveys. Nonserious participants should be allowed to render their data invalid, instead of letting their data invalidate the results.
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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.