Web Survey Bibliography
Title Improving Survey Research on the World-Wide Web Using the Randomized Response Technique
Author Musch, J., Broder, A., Klauer, K. C.
Source Dimensions of Internet Science, Reips, U.D., Bosnjak, M. (eds.), Pabst Science Publishers: Lengerich
Year 2001
Access date 28.05.2004
Full text pdf (88k)
Abstract The randomized response technique guarantees the anonymity of respondents in surveys aimed at determining the frequency of socially undesirable, embarrassing or criminal behavior. A random number generator (e.g., a dice or a coin) decides whether the respondent is asked to answer honestly to the critical question, or whether he or she is urged to answer with "yes", irrespective of the question content. The researcher does not know the outcome of the random experiment. Thus, he never knows whether an individual "yes"-answer was determined by the outcome of the dice throw, or whether the respondent actually exhibited the sensitive behavior. Using appropriate statistical procedures, the true proportion of respondents answering "yes" to the critical question can be determined. Validation studies show that sensitive behaviors are admitted to more often than in conventional surveys when the randomized response technique is being used. It is possible, however, that an unknown proportion of respondents does not answer as directed by the randomizing device. Such failure to obey to the rules of the randomized response technique (RRT) leads to an underestimation of the frequency of the sensitive behavior. Clark and Desharnais (1998) have therefore developed a method to determine the proportion of such cheating respondents. It combines conventional survey techniques with an experimental approach and is based on a between-subject manipulation of the applying random probabilites. The method allows to compute a confidence interval for the true value of the frequency of sensitive behaviors. Ideally, if the rules of the RRT are being followed (which can be tested), the method makes it possible determine the exact frequency of a socially undesirable, embarrassing, or criminal behavior of interest. In an exemplary experimental World-Wide Web survey, the frequency of tax evasion was determined using the cheating detection technique. As compared to a conventional survey, the results show an enhanced readiness to admit to tax fraud when the randomized response technique is being used. The question for tax fraud was nevertheless sensitive enough to lead some respondents into cheating. The experimental manipulation allowed to determine the proportion of cheaters, however, and a confidence interval for the true frequency of tax fraud could be calculated.
Access/Direct link Homepage - Universität Bonn (full text); Homepage - Pabst Science Publishers
Year of publication2001
Bibliographic typeBook section
Web survey bibliography - 2001 (57)
- Computer-assisted Self-interviewing over the Web: Criteria for Evaluating Survey Software with Reference...; 2001; Flatley, J.
- Creating a Web research guide: Collaboration between liaisons, faculty and students; 2001; Sugarman, T. S., Demetracopoulos, C.
- Questionnaire Pretesting Methods: Do Different Techniques and Different Organizations Produce Similar...; 2001; Rothgeb, J. M., Willis, G. B., Forsyth, B. H.
- Practical methods for sampling rare and mobile populations; 2001; Kalton, G.
- Recommended Standard Final Outcome Categories and Standard Definitions of Response Rate for Social Surveys...; 2001; Lynn, P., Beerten, R., Laiho, J., Martin, J.
- Visual Analog Scales: Do they have a role in the measurement of preferences for health states?; 2001; Torrance, G. W., Feeny, D., Furlong, W.
- Trends in household survey nonresponse: A longitudinal and international comparison; 2001; de Leeuw, E. D., de Heer, W.
- The construction of attitudes; 2001; Schwarz, N., Bohnerd, G.
- Subscale distance and item clustering effects in self-administered surveys: A new metric; 2001; Bradlow, E. T., Fitzsimons, G. J.
- On the use of college students in social science research: Insights from a second‐order meta...; 2001; Peterson, R. A.
- Introduction to behavioral research on the internet; 2001; Birnbaum, M. H.
- Experiments on column width spacing in the University of Michigan Student Life Survey; 2001; Boyd, C. J., McCabe, S. E., Couper, M. P., Crawford, S. D.
- Building an alternative response process model for business surveys; 2001; Willimack, D. K., Nichols, E. M.
- Ethische Dimensionen der Online-Forschung; 2001; Dzeyk, W.
- Panel Bias from Attrition and Conditioning: A Case Study of the Knowledge Networks Panel; 2001; Clinton, J. D.
- Web experiment on colour harmony principles applied to computer user interface design; 2001; Laugwitz, B.
- Knowledge acquisition, navigation and eye movements from text and hypertext; 2001; Naumann, A., Waniek, J., Krems, J. F.
- Score Reliability in Web or Internet-Based Surveys: Unnumbered Graphic Rating Scales versus Likert-Type...; 2001; Cook, C., Heath, F., Thompson, R. L., Thompson, B.
- On-line student feedback: A pilot study ; 2001; Galbraith, L. B., Gee, P., Jennings, F., Riley, R.
- Comparing Two Survey Research Approaches: E-Mail and Web-Based Technology versus Traditional Mail ; 2001; Howes, C. M., Mailloux, M. R.
- Literature Review of Web and E-mail Surveys, Chapter III; 2001; Schonlau, M., Fricker, R. D., Elliot, M. N.
- Over the Net. Taking advantage of the Internet in radio measurement; 2001; Cohen, E., O'Hare, B., Jones, L.
- Platform-dependent biases in Online Research: Do Mac users really think different?; 2001; Buchanan, T., Reips, U.-D.
- Documentation for 2001 Winter Internet Survey; 2001; Alvarez, M. R., Sherman, R.
- Using touch screen audio-CASI to obtain data on sensitive topics; 2001; Cooley, P. C., Rogers, S. M., Al-Tayyib, A. A., Ganapathi, L. F., Willis, G. B., Turner, C. F.
- When money doesn't talk; 2001; Funk, S., McCallum-Keeler, G.
- Reaching IT professionals: online vs. telephone interviewing; 2001; Van Houten, B.
- A comparison of Internet and mail survey methodologies; 2001; Medlin, B., Whitten, D.
- Qualitatively Speaking: Online focus groups are no substitute for the real thing; 2001; Greenbaum, T.
- Designing a questionnaire that dives beneath the surface; 2001; Humphreys, G., McNeish, J.
- Online focus group FAQs; 2001; Zinchiak, M.
- Telephone Survey Methodology; 2001; Groves, R. M., Biemer, P. P., Lyberg, L. E., Massey, J. T., Nicholls II, W. L., Waksberg, J.
- In the flesh or online? Exploring qualitative research methodologies; 2001; Seymour, W. S.
- Comparing Random Digit Dial Surveys With Web Surveys: The Case Of Health Care Consumers In California...; 2001; Berry, S., Zapert, K., Payne, S., Payne, L., Sanstad, K., Marcus, S., Spranca, M., Kan, H., Turner,...
- Analysis of Internet Users' Level of Online Privacy Concerns; 2001; O'Neil, D.
- Financial Incentives, Personal Information and Drop-Out in Online Studies; 2001; Frick, A., Bachtiger, M. T., Reips, U.-D.
- Survey Nonresponse; 2001; Groves, R. M., Dillman, D. A., Eltinge, J. L.
- Web survey errors; 2001; Lozar Manfreda, K.
- Testing an Internet Response Option for the American Community Survey; 2001; Griffin, D. H., Fischer, D. P., Morgan, M. T.
- Successful online qualitative market research; 2001; Bradford, D. P.
- From telephone to the Web; 2001; Stone, B.
- Best practices for online survey research; 2001; Dimetrosky, S., Khawaja, S., Degens, P.
- Scandinavia Leading Europe's Broadband Revolution; 2001; Anonymous
- Human factors in business-to-business research over the internet; 2001; Culkin, N., Brown, Js., Fletcher, J.
- Going Global: Issues in Applying Internet; 2001; Bauman, S., Jobity, N., Wilson, D., Atak, H., Deis, M., Airey, J.
- Experimental comparison of Web, electronic and mail survey technologies in operations management; 2001; Klassen, R. D., Jacobs, J.
- An Assessment of the Generalizability of Internet Surveys; 2001; Best, S. J., Krueger, B. S., Hubbard, C., Smith, A. J.
- Web survey design and administration; 2001; Couper, M. P., Traugott, M. W., Lamias, M. J.
- The record of internet-based opinion polls in predicting the results of 72 races in the November 2000...; 2001; Taylor, H., Bremer, J., Overmeyer, C., Siegel, J. W., Terhanian, G.
- Using Internet polling to forecast the 2000 elections; 2001; Terhanian, G., Taylor, H., Bremer, J., Overmeyer, C., Siegel, J. W.