An alternative to Kim and Warde's mixed randomized response model

• Autores: Housila P. Singh, Tanveer A. Tarray
• Localización: Sort: Statistics and Operations Research Transactions, ISSN 1696-2281, Vol. 37, Nº. 2, 2013, págs. 189-210
• Idioma: inglés
• Enlaces
  • Texto completo (pdf)
• Dialnet Métricas: 1 Cita
• Resumen

  • When open or direct surveys are about sensitive matters (e.g. gambling habits, addiction to drug and others intoxicants, alcoholism, proneness to tax invasion, induced abortions, drunken driving, history of past involvement in crimes, and homosexuality), non-response bias and response bias become serious problems because people oftentimes do not wish to give correct information. To reduce non-response and response bias, various alternative approaches have been proposed, for example a randomized response survey technique, or a mixed randomized response model using simple random sampling with a replacement sampling scheme that improves the privacy of respondents, proposed by authors Kim and Warde. In this paper we have suggested an alternative to Kim and Warde's mixed randomized response model to estimate the proportion of qualitative sensitive variable under the conditions presented in both the cases of completely truthful reporting and less than completely truthful reporting by the respondents. Properties of the proposed randomized response model have been studied along with recommendations. We have also extended the proposed model to stratified random sampling. Numerical illustrations and graphs are also given in support of the present study.

• Referencias bibliográficas
  • Chang, H. J. and Huang, K. C. (2001). Estimation of proportion and sensitivity of a qualitative character. Metrika, 53, 269–280.
  • Chaudhuri, A. and Mukerjee, R. (1988). Randomized Response: Theory and Techniques. Marcel-Dekker, New York, USA.
  • Cochran, W. G. (1977). Sampling Technique, 3rd Edition. New York: John Wiley and Sons, USA.
  • Fox, J. A. and Tracy, P. E. (1986). Randomized Response: A Method of Sensitive Surveys. Newbury Park, CA: SEGE Publications.
  • Greenberg, B., Abul-Ela, A., Simmons, W. R. and Horvitz, D. G. (1969). The unrelated question randomized response: Theoretical framework....
  • Greenberg, B., Kubller, R. R., Abernathy, J. R. and Horvitz, D. G. (1971). Applications of the RR technique in obtaining quantitative data....
  • Hong, K., Yum, J. and Lee, H. (1994). A stratified randomized response technique. Korean Journal of Applied Statistics, 7, 141–147.
  • Horvitz, D. G., Shah, B. V. and Simmons,W. R. (1967). The unrelated question randomized response model. Proceedings of the Social Statistics...
  • Kim, J. M., Tebbs, J. M. and An, S. W. (2006). Extensions of Mangat’s randomized response model. Journal of Statistical Planning and Inference,...
  • Kim, J. M. and Warde, W. D. (2004). A stratified Warner randomized response model. Journal of Statistical Planning and Inference, 120, 155–165.
  • Kim, J. M. and Warde, W. D. (2005). A mixed randomized response model. Journal of Statistical Planning and Inference, 133, 211–221.
  • Kim, J. M. and Elam, M. E. (2005). A two-stage stratified Warner’s randomized response model using optimal allocation. Metrika, 61, 1–7.
  • Kim, J. M. and Elam, M. E. (2007). A stratified unrelated randomized response model. Statistical Papers, 48, 215–233.
  • Lanke, J. (1976). On the degree of protection in randomized interview. International Statistical Review , 44, 80–83.
  • Mangat, N. S. and Singh, R. (1990). An alternative randomized procedure. Biometrika, 77, 439–442.
  • Mangat, N. S. (1994a). An improved randomized response strategy. Journal of the Royal Statistical Society, B, 56(1), 93–95.
  • Mangat, N. S. (1994b). An optional randomized response sampling technique. Journal of the Indian Statistical Association, 32(2), 71–75.
  • Mangat, N. S., Singh, R. and Singh, S. (1997). Violation of respondent’s privacy in Moors model-its rectification through a random group strategy...
  • Moors, J. A. (1971). Optimization of the unrelated question randomized response model. Journal of the American Statistical Association, 66,...
  • Nazuk, A. and Shabbir, J. (2010). A new mixed randomized response model. International Journal of Business and Social Science, 1, 186–190.
  • Ryu, J. B., Hong, K. H. and Lee, G. S. (1993). Randomized Response Model. Freedom. Academy, Seoul, Korea.
  • Singh, H. P. and Tarray, T. A. (2012). A stratified unknown repeated trials in randomized response sampling. Communication of the Korean Statistical...
  • Singh, H. P. and Tarray, T. A. (2013a). Two-stage stratified partial randomized response strategies. Accepted in Communication in Statistics...
  • Singh, H. P. and Tarray, T. A. (2013b). An alternative to stratified Kim and Warde’s randomized response model using optimal (Neyman) allocation....
  • Singh, H. P. and Tarray, T. A. (2013c). An improved mixed randomized response model. Model Assisted Statistical Application-Special-Issue...
  • Singh, R. andMangat, N. S. (1996). Elements of Survey Sampling, Kluwer Academic Publishers, Dordrecht, The Netherlands.
  • Singh, S. (2003). Advanced Sampling Theory with Applications. Kluwer Academic Publishers, Dordrecht, The Netherlands.
  • Sing, S., Singh, R. and Mangat, N. S. (2000). Some alternative strategies to Moor’s model in randomized response model. Journal of Statistical...
  • Tracy, D. S. and Mangat, N. S. (1996). Some developments in randomized response sampling during the last decade-A follow up of review by Chaudhuri...
  • Tracy, D. S. and Osahan, S. S. (1999). An improved randomized response technique. Pakistan Journal of Statistics, 15(1), 1–6.
  • Warner, S. L. (1965). Randomized response: A survey technique for eliminating evasive answer bias. Journal of the American Statistical Association,...