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Towards Candor, Cooperation, & Privacy in Applied Business Ethics Research: The Randomized Response Technique (RRT)

Published online by Cambridge University Press:  23 January 2015

Dan R. Dalton  and
Michael B. Metzger
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Abstract

Virtually every empirical inquiry of issues relevant to applied business ethics involves the asking of questions that are sensitive, embarrassing, threatening, stigmatizing, or incriminating. Accordingly, questions of this sort are likely to result in unsatisfactory outcomes: 1) many individuals will not respond; and/or, 2) many individuals will not respond candidly. An obvious objective, then, is to use a method to collect information which increases participation, provides absolute anonymity, and does not jeopardize subjects’ privacy. The randomized response technique (RRT) is a method designed to realize this promise. We provide here an overview of RRT approaches and applications which may be effectively used in empirical examinations of potentially sensitive issues in business ethics.

Type
Articles
Information
Business Ethics Quarterly , Volume 2 , Issue 2 , April 1992 , pp. 207 - 221
Copyright
Copyright © Society for Business Ethics 1992

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References

Abernathy, J. R., Greenberg, B. G., & Horvitz, D. G. (1970). Estimates of induced abortion in urban North Carolina. Demography, 7, 19–29.CrossRefGoogle ScholarPubMed
Abul-Ela, A. L., Greenberg, B. G., & Horvitz, D. G. (1967). A multiproportions randomized response model. Journal of the American Statistical Association, 62, 990–1008.Google Scholar
Adler, T. (1989). Integrity test popularity prompts close scrutiny. APA Monitor, 20 (12), p7., cited quote attributed to John Weintraub.Google Scholar
Administrative Science Quarterly, (1979). Qualitative methodology (special issue). Van Maanen, J. (Ed.).Google Scholar
Agar, M. H. (1986). Speaking of Ethnography. Beverly Hills, CA.: Sage Publications.Google Scholar
American Psychological Association. (1991). Questionnaires used in the prediction of trustworthiness in pre-employment selection decisions: An APA task force report.Google Scholar
Bergmann, T. J., Mündt, D. H., & Illgen, E. J. (1990). The evolution of honesty rights and means for their evaluation. Employee Responsibilities and Rights Journal, 3, 215–223.Google Scholar
Berry, L. E., Harwood, G. B., & Katz, J. L. (1987). Performance of auditing procedures by governmental auditors: Some preliminary evidence. The Accounting Review, 62, 14–28.Google Scholar
Boruch, R. F. (1972). Relations among statistical methods for assuring confidentiality of social research data. Social Science Research, 1, 403–414.CrossRefGoogle Scholar
Boruch, R. F., & Cecel, J. S. (1979). Assuring the confidentiality of social research data. Philadelphia, PA.: University of Pennsylvania Press.Google Scholar
Bourke, P. D. (1982). RR multivariate designs for categorical data. Communications in Statistics—Theory Methods, 11, 2889–2901.Google Scholar
Bourke, P. D., & Delanius, T. (1976). Some new ideas in the realm of randomized inquiries. International Statistical Review, 44, 219–221.Google Scholar
Buchman, T. A. (1983). The reliability of internal auditors” working papers. Auditing: A Journal of Practice & Theory, 3, 92–103.Google Scholar
Buchman, T. A., & Tracy, J. A. (1982). Obtaining responses to sensitive questions: Conventional questionnaire versus randomized response technique. Journal of Accounting Research, 20, 263–271.CrossRefGoogle Scholar
Chaudhuri, A., & Mukerjee, R. (1988). Randomized responses: Theory and techniques. New York: Marcel Dekker, Inc.Google Scholar
Cohen, J. 1988. Statistical Power Analysis for the Behavioral Sciences. Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
Cook, T. D. & Campbell, D. T. 1979. Quasi-Experimentation: Design & Analysis Issues for Field Studies. Boston: Houghton Mifflin.Google Scholar
Dowling, T. A., & Shachtman, R. (1975). On the relative efficiency of RR models. Journal of the American Statistical Association, 70, 84–87.Google Scholar
Duffy, J. C., & Waterton, J. J. (1984). RR models for estimating the distribution function of a quantitative character. International Statistical Review, 52, 165–171.Google Scholar
Durham, A. M., & Lichtenstein, M. J. (1983). Response bias in self-report surveys: Evaluation of randomized responses. In Waldo, G. P. (Ed.). Measurement issues in criminal justice. Beverly Hills, CA: Sage Publications.Google Scholar
Edgell, S. E., Himmelfarb, S., & Duchan, K. L. (1982). The validity of forced responses in a randomized response model. Sociological Methods and Research, 11, 89–100.Google Scholar
Eichhorn, B. H., & Hayre, L. S. (1983). Scrambled RR models for obtaining sensitive quantitative data. Journal of Statistical Planning and Inference, 1, 307–316.Google Scholar
Folsom, R. E., Greenberg, B. G., Horvitz, D. G., & Abernathy, J. R. (1973). The two alternate questions randomized response model for human surveys. Journal of the American Statistical Association, 68, 525–530.Google Scholar
Fox, J. A., & Tracy, P. E. (1986). Randomized response: A method for sensitive surveys. Beverly Hills, CA.: Sage Publications.CrossRefGoogle Scholar
Geurst, M. D., Andrus, R. R., & Reinmuth, J. (1975). Researching shoplifting and other deviant customer behavior using the randomized research design. Journal of Retailing, 51, 43–48.Google Scholar
Goodstadt, M. S., Cook, G., & Gruson, V. (1978). The validity of reported drug use: The randomized response technique. International Journal of Addictions, 13, 359–367.Google Scholar
Goodstadt, M. S., & Gruson, V. (1975). The randomized response technique: A test on drug use. Journal of the American Statistical Association, 70, 814–818.Google Scholar
Greenberg, B. G., Abul-Ela, A. A., Simmons, W. R., & Horvitz, D. G. (1969) The unrelated question RR model: Theoretical framework. Journal of the American Statistical Association, 64, 520–539.Google Scholar
Greenberg, B. G., Kubler, R. R., Abernathy, J. R., & Horvitz, D. G. (1971). Applications of the RR technique in obtaining quantitative data. Journal of the American Statistical Association, 66: 243–250.Google Scholar
Horvitz, D. G., Greenberg, B. G., & Abernathy, J. R. (1975). Recent developments in randomized response designs. In Srivastava, J. N. (Ed.) A survey of statistical design and linear models (pp. 271-285). New York: Elsevier Publishing.Google Scholar
Horvitz, D. G., Greenberg, B. G., & Abernathy, J. R. (1976). RR: A data gathering device for sensitive questions. International Statistical Review, 44, 181–196.Google Scholar
Hosseini, J. C., & Armacost, R. L. (1990). Randomized responses: A better way to obtain sensitive information. Business Horizons, 33 (3), 82–86.Google Scholar
I-Cheng, C., Chow, L. P., & Rider, R. V. (1972). The randomized response technique as used in the Taiwan outcome of pregnancy study. Studies in Family Planning, 2, 265–269.Google Scholar
Jones, J. W., Ash, P., & Soto, C. (1990). Employee privacy rights and pre-employment honesty tests. Employee Relations Law Journal, 15, 561–575.Google Scholar
Kirk, J., & Miller, M. L. (1986). Reliability and validity in qualitative research. Beverly Hills, CA: Sage Publications.Google Scholar
Kotz, S., & Stroup, D. F. (1983). Educated guessing: How to cope in an uncertain world. New York: Marcel Dekker.Google Scholar
Kraemer, H. C. & Thiemann, S. 1987. How Many Subjects: Statistical Power Analysis in Research Newbury Park, CA: Sage.Google Scholar
Leysieffer, F. W., & Warner, S. L. (1976). Respondent jeopardy and optimal designs in randomized response models. Journal of the American Statistical Association, 71, 649–656.CrossRefGoogle Scholar
Liu, P. T., & Chow, L. P. (1976). A new discrete quantitative RR model. Journal of the American Statistical Association. 71, 72–73.Google Scholar
Manhardt, P. J. (1989). Base rates and test of deception: Has I/O psychology shot itself in the foot? The Industrial-Organizational Psychologist, 26(2), 48–50.Google Scholar
Martin, S. L., & Terris, W. (1991). Predicting infrequent behavior: Clarifying the impact on false-positive rates. Journal of Applied Psychology, 76, 484–487.Google Scholar
Metzger, M. B. & Dalton, D. R. In Press. “Just Say No” To Integrity Testing. Journal of Law and Public Policy.Google Scholar
Moore, R. W., & Stewart, R. M. (1989). Evaluating employee integrity: Moral and methodological problems. Employee Responsibilities and Rights Journal, 2, 203–215.Google Scholar
Moors, J. J. (1971). Optimization and the unrelated question randomized response model. Journal of the American Statistical Association, 66, 627–629.Google Scholar
Murphy, K. R. (1987). Detecting infrequent deception. Journal of Applied Psychology, 72, 611–614.Google Scholar
Murphy, K. R. (1989). May be should shoot ourselves in the foot: Reply to Manhardt. The Industrial-Organizational Psychologist, 26(3), 45–46.Google Scholar
National Academy of Sciences. (1979). Report on the Panel on Privacy and Confidentiality as factors in survey response. Washington, DC: National Academy of Sciences.Google Scholar
Pollock, K. H., & Bek, Y. (1976). A comparison of three RR models for quantitative data. Journal of the American Statistical Association, 71, 884–886.Google Scholar
Poole, W. K. (1974). Estimation of the distribution function of a continuous type random variable through RR. Journal of the American Statistical Association, 69: 1002–1005.CrossRefGoogle Scholar
Poole, W. K., & Clayton, A. C. (1982). Generalizations of a contamination model for continuous type random variables. Communications is Statistics—Theory & Methods, 11: 1773–1742.Google Scholar
Reinmuth, J. E., & Geurts, M. D. (1975). The collection of sensitive information using a two-stage, randomized response model. Journal of Marketing Research, 402–407.Google Scholar
Rhode, J. G. (1977). Survey on the influence of selected aspects of the auditor's work environment on professional performance of certified public accountants: A study and report for the Commission on auditor's responsibilities. New York: AICPA.Google Scholar
Rosenthal, R., & Rosnow, R. L. (1984). Essentials of behavioral research. New York: McGraw Hill.Google Scholar
Sackett, P. R., Burris, L. R., & Callahan, C. (1989). Integrity testing for personnel selection: An update. Personnel Psychology, 42, 491–528.CrossRefGoogle Scholar
Schneider, A., & Wilner, N. (1990). A test of audit deterrent to financial reporting irregularities using the randomized response technique. The Accounting Review, 65, 668–681.Google Scholar
Schuman, H., & Kalton, G. (1985). Survey methods. In Lindzey, G. and Aronson, E. (Eds.). The Handbook of Social Psychology (pp. 635–698. New York: Random House.Google Scholar
Shimizu, I. M., & Bonham, G. S. (1978). Randomized response technique in a national survey. Journal of the American Statistical Association, 73, 35–39.Google Scholar
Steeh., C. G. (1981). Trends in nonresponse rates, 1952-1979 Public Opinion Quarterly, 45, 40–57.Google Scholar
Stone, E. F. (1978). Research methods in organizational behavior. Santa Monica, CA: Goodyear Publishing.Google Scholar
Tamhane, A. C. (1981). RR techniques for multiple sensitive attributes. Journal of the American Statistical Association, 76, 916–923.Google Scholar
Tracy, P. E., & Fox, J. A. (1981). The validity of randomized response for sensitive measurements. American Sociological Review, 46, 187–200.CrossRefGoogle Scholar
U. S. Congress. (1991). The use of integrity tests for pre-employment screening. Office of Technical Assistance. Washington, DC: United States Printing Office.Google Scholar
Van Manaan, J., Dabbs, J. M., & Faulkner, R. R. (1982) Varieties of qualitative research. Beverly Hills, CA: Sage Publications.Google Scholar
Warner, S. L. (1965). RR: A survey technique for eliminating evasive answer bias. Journal of the American Statistical Association, 60, 63–69.Google Scholar
Warner, S. L. (1971). The linear RR model. Journal of the American Statistical Association, 66: 884–888.CrossRefGoogle Scholar
Webb, E. J., Campbell, D. T., Sehwartz, R. D., Sechrest, L., & Grove, J. B. (1981). Nonreactive measures in the social sciences. Boston, MA.: Houghton Mifflin.Google Scholar
Zdep, S. M. & Rhodes (1976). Making the randomized response technique work. Public Opinion Quarterly, 40, 531–537.Google Scholar