Indirect questioning in sample surveys

Indirect Questioning in Sample Surveys

Volumn , Issue , 2013, Pages 1-177

  Chaudhuri, Arijit ^a   Christofides, Tasos C ^b  

^a INDIAN STATISTICAL INSTITUTE   (India)

^b UNIVERSITY OF CYPRUS   (Cyprus)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84929936568     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-3-642-36276-7     Document Type: Book

References (221)

1. Abul-Ela, Abdel-Latif, A., Greenberg, B. G., Horvitz, D. G. (1967). A multi-proportion randomized response model. Journal of the American Statistical Association, 62, 990-1008.
2. Arnab, R. (1995). Optimal estimation of a finite population total under randomized response surveys. Statistics, 27, 175-180.
3. Bar-Lev Shaul, K., Bobovitch, E., Boukai, B. (2004). A note on randomized response models for quantitative data. Metrika, 60, 255-260.
4. Blank, S., & Gavin, M. (2009). The randomized response technique as a tool for estimating noncompliance rates in fisheries: a case study of illegal red abalone (Haliotis rufescens) fishing in Northern California. Environmental Conservation, 36, 112-119.
5. Boruch, R. F. (1972). Relations among statistical methods for assuring confidentiality of social research data. Social Science Research, 1, 403-414.
6. Bouza, C. N. (2009). Ranked set sampling and randomized response procedures for estimating the mean of a sensitive quantitative character. Metrika, 70, 267-277.
7. Chaudhuri, A. (1987). Randomized response surveys of finite populations: a unified approach with quantitative data. Journal of Statistical Planning and Inference, 15, 157-165.
8. Chaudhuri, A. (2011). Randomized response and indirect questioning techniques in surveys. Boca Raton: Chapman & Hall, CRC Press, Taylor & Francis Group.
9. Coutts, E., Jann, B., Ivar, K., Anatol-Fiete, N. (2011). Plagiarism in student papers: prevalence estimates using special techniques for sensitive questions. Journal of Economics and Statistics, 231, 749-760.
10. Diana, G., & Perri, P. F. (2011). A class of estimators for quantitative sensitive data. Statistical Papers, 52, 633-650.
11. Dietz, P., Striegel, H., Franke, G. A., Lieb, K., Simon, P., Ulrich, R. (2013). Randomized response estimates for the 12-month prevalence of cognitive-enhancing drug use in university students. Pharmacotherapy, 33, 44-50.
12. Franke, G. A., Bagusat, C., Dietz, P., Hoffmann, I., Simon, P., Ulrich, R., Lieb, K. (2013). Use of illicit and prescription drugs for cognitive or mood enhancement among surgeons. MBC Medicine, doi:10.1186/1741-7015-11-102.
13. Greenberg, B. G., Abul-Ela, A.-L. A., Simmons, W. R., Horvitz, D. G. (1969). The unrelated question RR model: theoretical framework. Journal of the American Statistical Association, 64, 520-539.
14. Greenberg, B. G., Kuebler, R. R., Abernathy, J. R., Horvitz, D. G. (1971). Application of randomized response technique in obtaining quantitative data. Journal of the American Statistical Association, 66, 243-250.
15. Hejri, M. S., Zendehdel, K., Asghari, F., Fotouhi, A., Rashidian, A. (2013). Academic disintegrity among medical students: a randomized response technique study. Medical Education, 47, 144-153.
16. Huang, K.-C., Lan, C.-H., Kuo, M.-P. (2006). Estimation of sensitive quantitative characteristics in randomized response sampling. Journal of Statistics and Management Systems, 9, 27-35.
17. Jann, B., Jerke, J., Krumpal, I. (2012). Asking sensitive questions using the crosswise model. An experimental survey measuring plagiarism. Public Opinion Quarterly, 76, 32-49.
18. John, F. A. V. St., Edwards-Jones, G., Gibbons, J. M., Jones, J. P. G. (2010). Testing novel methods for assessing rule breaking in conservation. Biological Conservation, 143, 1025-1030.
19. Karlan, D. S., & Zinman, J. (2012). List randomization for sensitive behavior: an application for measuring use of loan proceeds. Journal of Developmental Economics, 98, 71-75.
20. Kerkvliet, J. (1994). Estimating a logit model with randomized data: the case of cocaine use. Australian Journal of Statistics, 36, 9-20.
21. Kuha, J., & Jackson, J. (2013). The item count method for sensitive survey questions: modelling criminal behavior. Journal of the Royal Statistical Society: Series C (Applied Statistics), forthcoming.
22. Kuk Anthony, Y. C. (1990). Asking sensitive questions indirectly. Biometrika, 77, 436-438.
23. Krumpal, I. (2012). Estimating the prevalence of xenophobia and anti-Semitism in Germany: a comparison of randomized response and direct questioning. Social Science Research, 41, 1387-1403.
24. Maddala, G. S. (1983). Limited dependent and qualitative variables in econometrics. New York: Cambridge University Press.
25. Pal, S. (2008). Unbiasedly estimating the total of a stigmatizing variable from a complex survey on permitting options for direct or randomized responses. Statistical Papers, 49, 157-164.
26. Pitsch, W., Emrich, E., Klein, M. (2007). Doping in elite sports in Germany: results on www survey. European Journal of Sport and Society, 4, 89-102.
27. Saha, A. (2008). A randomized response technique for quantitative data under unequal probability sampling. Journal of Statistical Theory and Practice, 2, 589-596.
28. Scheers, N. J. (1992). A review of randomized response techniques. Measurement and Evaluation in Counseling and Development, 25, 27-41.
29. Sen, P. K. (1974). On unbiased estimation for randomized response models. Journal of the American Statistical Association, 69, 997-1001.
30. Singh, S., Mahmood, M., Tracy, D. S. (2001). Estimation of mean and variance of stigmatized quantitative variable using distinct units in randomized response sampling. Statistical Papers, 42, 403-411.
31. Striegel, H., Simon, P., Hansel, J., Niess, A. M., Ulrich, R. (2006). Doping and drug use in elite sports: an analysis using the randomized technique. Medicine and Science in Sports and Exercise, 38, 247.
32. Striegel, H., Ulrich, R., Simon, P. (2010). Randomized response estimates for doping and illicit drug use in elite athletes. Drug and Alcohol Dependence, 106, 230-232.
33. Umesh, U. N., & Peterson, R. A. (1991). A critical evaluation of the randomized response method. Social Methods Research, 20, 104-138.
34. Van Der Heijden, P. G. M., & Van Gils, G. (1996). Some logistic regression models for randomized response data. In Proceedings of the 11th International Workshop on Statistical Modelling, Orvieto, Italy.
35. Van Der Heijden, P. G. M., Van Gils, G., Bouts, J., Hox, J. (2000). A comparison of randomized response, Computer assisted Self Interview, and Face to Face Direct Questioning; eliciting sensitive information in the context of welfare and unemployment benefits. Sociological Methods and Research, 28, 505-537.
36. Warner Stanley, L. (1965). Randomized Response: a survey technique for eliminating evasive answer bias. Journal of the American Statistical Association, 60, 63-69.
37. Basu, D. (1971). An essay on the logical foundations of survey sampling, Part 1. In V. P. Godambe, D. A. Sprott (Eds.), Foundations of statistical inference (pp. 203-242). Toronto: Holt, Rinehart & Winston.
38. Chaudhuri, A. (2010). Essentials of survey sampling. New Delhi: Prentice Hall of India.
39. Chaudhuri, A. (2011). Randomized response and indirect questioning techniques in surveys. Boca Raton: Chapman & Hall, CRC Press, Taylor & Francis Group.
40. Godambe, V. P. (1955). A unified theory of sampling from finite populations. Journal of the Royal Statistical Society: Series B, 17, 269-278.
41. Hajek, J. (1971). Comment on a paper by Basu. In V. P. Godambe, D. A. Sprott (Eds.), Foundations of statistical inference (pp. 203-242). Toronto: Holt, Rinehart and Winston.
42. Hanurav, T. V. (1966). Some aspects of unified sampling theory. Sankhya, Series A, 28, 175-204.
43. Hege, V. S. (1965). Sampling designs which admit uniformly minimum unbiased estimators. Calcutta Statistical Association Bulletin, 14, 160-162.
44. Horvitz, D. G., & Thompson, D. J. (1952). A generalization of sampling without replacement from finite universe. Journal of Americal Statistical Association, 47, 663-685.
45. Lanke, J. (1975). Some contributions to the theory of survey sampling. Ph. D. Thesis, University of Lund, Lund, Sweden.
46. Neyman, J. (1934). On the two different aspects of the representative method: the method of stratified sampling and the method of purposive selection. Journal of the Royal Statistical Society: Series B, 97, 199-214.
47. Yates, F., & Grundy, P. M. (1953). Selection without replacement from within strata with probability proportional to size. Journal of the Royal Statistical Society: Series B, 15, 253-261.
48. Chaudhuri, A. (2001a). Using randomized response from a complex survey to estimate a sensitive proportion in a dichotomous finite population. Journal of Statistical Planning and Inference, 94, 37-42.
49. Chaudhuri, A. (2001b). Estimating sensitive proportions from unequal probability samples using randomized responses. Pakistan Journal of Statistics, 17, 259-270.
50. Chaudhuri, A. (2010). Essentials of survey sampling. New Delhi: Prentice Hall of India.
51. Chaudhuri, A. (2011). Randomized response and indirect questioning techniques in surveys. Boca Raton: Chapman & Hall, CRC Press, Taylor & Francis Group.
52. Chaudhuri, A., & Christofides, T. C. (2008). Indirect questioning: how to rival randomized response techniques. International Journal of Pure and Applied Mathematics, 43, 283-294.
53. Christofides, T. C. (2009). Randomized response without a randomization device. Advances and Applications in Statistics, 11, 15-28.
54. Droitcour, J. A., Larson, E. M., Scheuren, F. J. (2001). The three card method: estimating sensitive items with permanent anonymity of response. In Proceedings of the Social Statistics Section of the American Statistical Association. Alexandria, VA: ASA.
55. Esponda, F. (2006). Negative surveys. arXiv:ST/0608176v1
56. Esponda, F., & Guerrero, V. M. (2009). Surveys with negative questions for sensitive items. Statistics and Probability Letters, 79, 2456-2461.
57. Miller, J. D. (1985). The nominative technique: a new method of estimating heroin prevalence. NIDA Research Monograph, (57), 104-124.
58. Miller, J. D., Cisin, I. H., Harrel, A. V. (1986). A new technique for surveying deviant behavior: item count estimates of marijuana, cocaine and heroin. Paper presented at the annual meeting of the American Association for Public Opinion Research, St. Petersburg, Florida.
59. Tan, M. T., Tian, G. L., Tang, M. L. (2009). Sample surveys with sensitive questions: a nonrandomized response approach. American Statistician, 63, 9-16.
60. Tian, G.-L., Yu, J.-W., Tang, M.-L., Geng, Z. (2007). A new nonrandomized model for analyzing sensitive questions with binary outcomes. Statistics in Medicine, 26, 4238-4252.
61. Warner, S. L. (1965). Randomized Response: a survey technique for eliminating evasive answer bias. Journal of the American Statistical Association, 60, 63-69.
62. Yu, J.-W., Tian, G.-L., Tang, M.-L. (2008). Two new models for survey sampling with sensitive characteristic: design and analysis. Metrika, 67, 251-263.
63. Alhassan, A. W., Ohuchi, S., Taguri, M. (1991). Randomized response designs considering the probability of dishonest answers. Journal of the American Statistical Association, 4, 1-24.
64. Arnab, R. (2004). Optional randomized response techniques for complex survey designs. Biometrical Journal, 46, 114-124.
65. Bar-Lev, S. K., Bobovitch, E., Boukai, B. (2003). A common conjugate prior structure for several randomized response models. Test, 12, 101-113.
66. Barabesi, L., Franceschi, S., Marcheselli, M. (2012). A randomized response procedure for multiple sensitive questions. Statistical Papers, 53, 703-718.
67. Barabesi, L., & Marcheselli, M. (2006). A practical implementation and Bayesian estimation in Franklin's randomized response procedure. Communication in Statistics-Simulation and Computation, 35, 563-573.
68. Barabesi, L., & Marcheselli, M. (2010). Bayesian estimation of proportion and sensitivity level in randomized response procedures. Metrika, 72, 75-88.
69. Basu, D. (1969). Role of the sufficiency and likelihood principles in sample survey theory. Sankhya, Series A, 31, 441-454.
70. Boruch, R. F. (1972). Relations among statistical methods for assuring confidentiality of social research data. Social Science Research, 1, 403-414.
71. Bourke, P. D. (1981). On the analysis of some multivariate randomized response designs for categorical data. Journal of Statistical Planning and Inference, 5, 165-170.
72. Chang, H.-J., Wang, C.-L., Huang, K.-C. (2004). Using randomized response to estimate the proportion and truthful reporting probability in a dichotomous finite population. Journal of Applied Statistics, 31, 565-573.
73. Chaudhuri, A. (2001a). Using randomized response from a complex survey to estimate a sensitive proportion in a dichotomous finite population. Journal of Statistical Planning and Inference, 94, 37-42.
74. Chaudhuri, A. (2001b). Estimating sensitive proportions from unequal probability samples using randomized responses. Pakistan Journal of Statistics, 17, 259-270.
75. Chaudhuri, A. (2002). Estimating sensitive proportions from randomized responses in unequal probability sampling. Calcutta Statistical Association Bulletin, 52, 315-322.
76. Chaudhuri, A. (2004). Christofides' randomized response technique in complex surveys. Metrika, 60, 223-228.
77. Chaudhuri, A. (2010). Essentials of survey sampling. New Delhi: Prentice Hall of India.
78. Chaudhuri, A. (2011). Randomized response and indirect questioning techniques in surveys. Boca Raton: Chapman & Hall, CRC Press, Taylor & Francis Group.
79. Chaudhuri, A., Adhikary, A. K., Dihidar, S. (2000). Mean square error estimation in multi-stage sampling. Metrika, 52, 115-131.
80. Chaudhuri, A., & Mukerjee, R. (1988). Randomized response: theory and techniques. New York: Marcel Dekker.
81. Chaudhuri, A., & Saha, A. (2005). Optional versus compulsory randomized response techniques in complex surveys. Journal of Statistical Planning and Inference, 135, 516-527.
82. Christofides, T. C. (2003). A generalized randomized response technique. Metrika, 57, 195-200.
83. Christofides, T. C. (2005a). Randomized response in stratified sampling. Journal of Statistical Planning and Inference, 128, 303-310.
84. Christofides, T. C. (2005b). Randomized response technique for two sensitive characteristics at the same time. Metrika, 62, 53-63.
85. Cruyff, M. J. L. F., Bockenholt, U., Van Der Hout, A., Van Der Heijden, P. G. M. (2008). Accounting for self-protective responses in randomized response data from social security survey using the zero-inflated Poisson model. Annals of Applied Statistics, 2, 316-331.
86. Dalenius, T., & Vitale, R. A. (1974). A new RR design for estimating the mean of a distribution. Technical Report, No 78, Brown University, Providence, RI.
87. Devore, J. L. (1977). A note on the randomized response technique. Communications in Statistics -Theory and Methods, 6, 1525-1529.
88. Ericson, W. A. (1969). Subjective Bayesian models in sampling finite populations. Journal of the Royal Statistical Society: Series B, 31, 195-233.
89. Fligner, M. A., Policello, G. E., Singh, J. (1977). A comparison of two survey methods with consideration for the level of respondent protection. Communications in Statistics -Theory and Methods, 6, 1511-1524.
90. Fox, J. A., & Tracy, P. E. (1986). Randomized response: a method for sensitive surveys. London: Sage.
91. Franklin, L. A. (1989). A comparison of estimators for randomized response sampling with continuous distributions from a dichotomous population. Communications in Statistics -Theory and Methods, 18, 489-505.
92. Gelfand, A. E., & Smith, A. F. M. (1990). Sampling-based approaches to calculating marginal densities. Journal of the American Statistical Association, 85, 398-409.
93. Godambe, V. P. (1955). A unified theory of sampling from finite populations. Journal of the Royal Statistical Society: Series B, 17, 269-278.
94. Greenberg, B. G., Abul-Ela, A.-L. A., Simmons, W. R., Horvitz, D. G. (1969). The unrelated question RR model: theoretical framework. Journal of the American Statistical Association, 64, 520-539.
95. Gupta, S., & Shabbir, J. (2007). On the estimation of population mean and sensitivity in two-stage optional randomized response model. Journal of the Indian Society of Agricultural Statistics, 61, 164-168.
96. Gupta, S., Shabbir, J., Sehra, S. (2010). Mean and sensitivity estimation in optional randomized response models. Journal of Statistical Planning and Inference, 140, 2870-2874.
97. Hastings, W. K. (1970). Monte Carlo sampling methods using Markov Chains and their applications. Biometrika, 57, 97-109.
98. Hong, K., Yum, J., Lee, H. (1994). A stratified randomized response technique. Korean Journal of Applied Statistics, 7, 141-147.
99. Horvitz, D. G., Shah, B. V., Simmons, W. R. (1967). The unrelated question RR model. Proceedings of the Social Statistics Section of the American Statistical Association (pp. 65-72). Alexandria, VA: ASA.
100. Horvitz, D. G., & Thompson, D. J. (1952). A generalization of sampling without replacement from finite universe. Journal of the American Statistical Association, 47, 663-685.
101. Huang, K.-C. (2004). A survey technique for estimating the proportion and sensitivity in a dichotomous finite population. Statistica Neerlandica, 58, 75-82.
102. Huang, K.-C. (2008). Estimation for sensitive characteristics using optional randomized response technique. Quality and Quantity, 4, 679-686.
103. Hussain, Z., & Shabbir, J. (2009). Bayesian estimation of population proportion of a sensitive characteristic using simple beta prior. Pakistan Journal of Statistics, 25, 27-35.
104. Kim, J.-M., & Elam, M. E. (2007). A stratified unrelated question randomized response model. Statistical Papers, 48, 215-233.
105. Kim, J.-M., & Heo, T.-Y. (2013). Randomized response group testing model. Journal of Statistical Theory and Practice, 7, 33-48.
106. Kim, J.-M., Tebbs, J. M., An, S.-W. (2006). Extensions of Mangat's randomized response model. Journal of Statistical Planning and Inference, 136, 1554-1567.
107. Kim, J.-M., & Warde, W. D. (2004). A stratified Warner's randomized response model. The Journal of Statistical Planning and Inference, 120, 155-165.
108. Kuk, A. Y. C. (1990). Asking sensitive questions indirectly. Biometrika, 77, 436-438.
109. Lakshmi, D. V., & Raghavarao, D. (1992). A test for detecting untruthful answering in randomized response procedures. Journal of Statistical Planning and Inference, 31, 387-390.
110. Land, M., Singh, S., Sedory, S. A. (2012). Estimation of a rare sensitive attribute using Poisson distribution. Statistics, doi: 10.1080/02331888.2010.524300.
111. Lee, C.-S., Sedory, S. A., Singh, S. (2013). Estimating at least seven measures of qualitative variables from a single sample using randomized response technique. Statistics and Probability Letters, 83, 399-409.
112. Lee, G.-S., Uhm, D., Kim, J.-M. (2012). Estimation of a rare sensitive attribute in a stratified sample using Poisson distribution. Statistics, doi:10.1080/02331888.2011.625503.
113. Liu, P. T., Chow, L. P., Mosley, W. H. (1975). Use of RR technique with a new randomizing device. Journal of the American Statistical Association, 70, 329-332.
114. Mangat, N. S. (1991). An optional randomized response sampling technique using nonstigmatized attribute. Statistics, 51, 595-602.
115. Mangat, N. S. (1992). Two stage randomized response sampling procedure using unrelated question. Journal of the Indian Society of Agricultural Statistics, 44, 82-87.
116. Mangat, N. S. (1994). An improved randomized response strategy. Journal of the Royal Statistical Society: Series B, 56, 93-95.
117. Mangat, N. S., & Singh, R. (1990). An alternative randomized response procedure. Biometrika, 77, 439-442.
118. Mangat, N. S., Singh, R., Singh, S. (1992). An improved unrelated question randomized response strategy. Calcutta Statistical Association Bulletin, 42, 277-281.
119. Mangat, N. S., & Singh, S. (1994). An optional randomized response sampling technique. Journal of the Indian Statistical Association, 32, 71-75.
120. Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., Teller, E. (1953). Equations of state calculations by fast computing machines. Journal of Chemical Physics, 21, 1087-1092.
121. Migon, H. S., & Tachibana, V. M. (1997). Bayesian approximations in randomized response model. Computational Statistics and Data Analysis, 24, 401-409.
122. Moshagen, M., & Musch, J. (2011). Surveying multiple sensitive attributes using an extension of the randomized response technique. International Journal of Public Opinion Research, doi:10.1093/ijpor/edr034.
123. O'Hagan, A. (1987). Bayes linear estimators for randomized response models. Journal of the American Statistical Association, 82, 580-585.
124. Pitz, G. F. (1980). Bayesian analysis of random response models. Psychological Bulletin, 87, 209-212.
125. Rao, J. N. K., Hartley, H. O., Cochran, W. G. (1962). On the simple procedure of unequal probability sampling without replacement. Journal of the Royal Statistical Society: Series B, 24, 482-491.
126. Saha, A. (2011). An optional scrambled randomized response technique for practical surveys. Metrika, 73, 139-149.
127. Singh, S., & Grewal, I. S. (2013). Geometric distribution as a randomization device: implemented to the Kuk's model. International Journal of Contemporary Mathematical Sciences, 8, 243-248.
128. Singh, S., & Joarder, A. H. (1997a). Unknown repeated trials in randomized response sampling. Journal of the Indian Statistical Association, 30, 109-122.
129. Singh, S., & Joarder, A. H. (1997b). Optional randomized response technique for sensitive quantitative variable. Metron, 55, 151-157.
130. Tamhane, A. C. (1981). Randomized response techniques for multiple sensitive attributes. Journal of the American Statistical Association, 76, 916-923.
131. Tierney, L., & Kadane, J. B. (1986). Accurate approximations for posterior moments and marginal densities. Journal of the American Statistical Association, 81, 82-86.
132. Unnikrishnan, N. K., & Kunte, S. (1999). Bayesian analysis for randomized response models. Sankhya Series B, 61, 422-432.
133. Walpole, R. E., & Myers, R. H. (1993). Probability and statistics for engineers and scientists, 5th edn. Englewood Cliffs, NJ: Prentice-Hall.
134. Warner, S. L. (1965). Randomized Response: a survey technique for eliminating evasive answer bias. Journal of the American Statistical Association, 60, 63-69.
135. Winkler, R. L., & Franklin, L. A. (1979). Warner's randomized response model: a Bayesian approach. Journal of the American Statistical Association, 74, 207-214.
136. Yates, F., & Grundy, P. M. (1953). Selection without replacement from within strata with probability proportional to size. Journal of the Royal Statistical Society: Series B, 15, 253-261.
137. Arnab, R. (2004). Optional randomized response techniques for complex survey designs. Biometrical Journal, 46, 114-124.
138. Chaudhuri, A. (1992). Randomized response: Estimating mean square errors of linear estimators and finding optimal unbiased strategies. Metrika, 39, 341-357.
139. Chaudhuri, A. (2011). Randomized response and indirect questioning techniques in surveys. Boca Raton: Chapman & Hall, CRC Press, Taylor & Francis Group.
140. Chaudhuri, A., & Dihidar, K. (2009). Estimating means of stigmatizing qualitative and quantitative variables from discretionary responses randomized or direct. Sankhya Series B, 71, 123-136.
141. Chaudhuri, A., & Mukerjee, R. (1985). Optionally randomized response techniques. Calcutta Statistical Association Bulletin, 34, 225-229.
142. Chaudhuri, A., & Mukerjee, R. (1988). Randomized response: theory and techniques. New York: Marcel Dekker.
143. Chaudhuri, A., & Saha, A. (2005). Optional versus compulsory randomized response techniques in complex surveys. Journal of Statistical Planning and Inference, 135, 516-527.
144. Eichhorn, B. H., & Hayre, L. S. (1983). Scrambled randomized response methods for obtaining quantitative data. Journal of Statistical Planning and Inference, 7, 306-316.
145. Gupta, S., Gupta, B., Singh, S. (2002). Estimation of sensitivity level of personal interview survey question. Journal of Statistical Planning and Inference, 100, 239-247.
146. Gupta, S., Shabbir, J., Sehra, S. (2010). Mean and sensitivity estimation in optional randomized response models. Journal of Statistical Planning and Inference, 140, 2870-2874.
147. Huang, K.-C. (2010). Unbiased estimators of mean, variance and sensitivity level for quantitative characteristics in finite population sampling. Metrika, 71, 341-352.
148. Pal, S. (2008). Unbiasedly estimating the total of a stigmatizing variable from a complex survey on permitting options for direct or randomized responses. Statistical Papers, 49, 157-164.
149. Rao, J. N. K., Hartley, H. O., Cochran, W. G. (1962). On the simple procedure of unequal probability sampling without replacement. Journal of the Royal Statistical Society: Series B, 24, 482-491.
150. Biemer, P., & Brown, G. (2005). Model-based estimation of drug prevalence using item count data. Journal of Official Statistics, 21, 287-308.
151. Chaudhuri, A. (2000). Network and adaptive sampling with unequal probabilities. Calcutta Statistical Association Bulletin, 50, 237-253.
152. Chaudhuri, A. (2012). Unbiased estimation of a sensitive proportion in general sampling by three non-randomized response schemes. Journal of Statistical Theory and Practice, 6, 376-381.
153. Chaudhuri, A., Bose, M., Dihidar, K. (2005). Sample size restrictive adaptive sampling: an application in estimating localized elements. Journal of Statistical Planning and Inference, 134, 254-267.
154. Chaudhuri, A., Bose, M., Ghosh, J. K. (2004). An application of adaptive sampling to estimate highly localized population segments. Journal of Statistical Planning and Inference, 121, 175-189.
155. Chaudhuri, A., & Christofides, T. C. (2007). Item count technique in estimating the proportion of people with a sensitive feature. Journal of Statistical Planning and Inference, 137, 589-593.
156. Chaudhuri, A., & Christofides, T. C. (2008). Indirect questioning: how to rival randomized response techniques. International Journal of Pure and Applied Mathematics, 43, 283-294.
157. Chaudhuri, A., & Mukerjee, R. (1988). Randomized response: theory and techniques. New York: Marcel Dekker.
158. Chaudhuri, A., & Pal, S. (2002). On certain alternative mean square error estimators in complex survey sampling. Journal of Statistical Planning and Inference, 104, 363-375.
159. Christofides, T. C. (2009). Randomized response without a randomization device. Advances and Applications in Statistics, 11, 15-28.
160. Coutts, E., & Jann, B. (2011). Sensitive questions in online surveys: experimental results for the randomized response technique (RRT) and the unmatched count technique (UCT). Sociological Methods & Research, 40, 169-193.
161. Coutts, E., Jann, B., Ivar, K., Anatol-Fiete, N. (2011). Plagiarism in student papers: prevalence estimates using special techniques for sensitive questions. Journal of Economics and Statistics, 231, 749-760.
162. Droitcour, J. A., Larson, E. M., Scheuren, F. J. (2001). The three card method: estimating sensitive items with permanent anonymity of response. In Proceedings of the Social Statistics Section of the American Statistical Association. Alexandria, VA: ASA.
163. Eichhorn, B. H., & Hayre, L. S. (1983). Scrambled randomized response methods for obtaining quantitative data. Journal of Statistical Planning and Inference, 7, 306-316.
164. Esponda, F. (2006). Negative surveys. arXiv:ST/0608176v1
165. Esponda, F., & Guerrero, V. M. (2009). Surveys with negative questions for sensitive items. Statistics and Probability Letters, 79, 2456-2461.
166. Gupta, S., Gupta, B., Singh, S. (2002). Estimation of sensitivity level of personal interview survey question. Journal of Statistical Planning and Inference, 100, 239-247.
167. Hejri, M. S., Zendehdel, K., Asghari, F., Fotouhi, A., Rashidian, A. (2013). Academic disintegrity among medical students: a randomized response technique study. Medical Education, 47, 144-153.
168. Horvitz, D. G., & Thompson, D. J. (1952). A generalization of sampling without replacement from finite universe. Journal of the American Statistical Association, 47, 663-685.
169. Huang, K.-C. (2010). Unbiased estimators of mean, variance and sensitivity level for quantitative characteristics in finite population sampling. Metrika, 71, 341-352.
170. Hussain, Z., & Shabbir, J. (2011). On item count technique in survey sampling. Journal of Informatics and Mathematical Sciences, 2, 161-169.
171. Imai, K. (2011). Multivariate regression analysis for the item count technique. Journal of the American Statistical Association, 106, 407-415.
172. Jann, B., Jerke, J., Krumpal, I. (2012). Asking sensitive questions using the crosswise model: an experimental survey measuring plagiarism. Public Opinion Quarterly, 76, 32-49.
173. John, F. A. V. St., Edwards-Jones, G., Gibbons, J. M., Jones, J. P. G. (2010). Testing novel methods for assessing rule breaking in conservation. Biological Conservation, 143, 1025-1030.
174. Krebs, C. P., Lindquist, C. H., Warner, T. D., Fisher, B. S., Martin, S. L., Childers, J. M. (2011). Comparing sexual assault prevalence estimates obtained with direct and indirect questioning techniques. Violence Against Women, 17, 219-235.
175. Kutnik, B., Belser, P., Danailova-Trainor, G. (2007). Methodologies for global and national estimation of human trafficking victims: current and future approaches. In Working paper 29, International Labour Office, Geneva.
176. Miller, J. D. (1984). A new survey technique for studying deviant behavior. Ph. D. Thesis, The George Washington University.
177. Miller, J. D. (1985). The nominative technique: a new method of estimating heroin prevalence. NIDA Research Monograph, No. 57, 104-124.
178. Miller, J. D., Cisin, I. H., Harrel, A. V. (1986). A new technique for surveying deviant behavior: item count estimates of marijuana, cocaine and heroin. Paper presented at the annual meeting of the American Association for Public Opinion Research, St. Petersburg, Florida.
179. Pal, S. (2007). Estimating the proportion of people bearing a sensitive issue with an option to item count lists and randomized response. Statistics in Transition, 8, 301-310.
180. Raghavarao, D., & Federer, W. F. (1979). Block total response as an alternative to the randomized response method in surveys. Journal of the Royal Statistical Society: Series B, 41, 40-45.
181. Tan, M. T., Tian, G. L., Tang, M. L. (2009). Sample surveys with sensitive questions: a nonrandomized response approach. American Statistician, 63, 9-16.
182. Tian, G.-L., Yu, J.-W., Tang, M.-L., Geng, Z. (2007). A new nonrandomized model for analyzing sensitive questions with binary outcomes. Statistics in Medicine, 26, 4238-4252.
183. Thompson, S. K. (1992). Sampling. New York: Wiley.
184. Thompson, S. K., & Seber, G. A. F. (1996). Adaptive sampling. New York: Wiley.
185. Tsuchiya, T., & Hirai, Y. (2010). Elaborate item count questioning: why do people underreport in item count responses? Survey Research Methods, 4, 139-149.
186. Yates, F., & Grundy, P. M. (1953). Selection without replacement from within strata with probability proportional to size. Journal of the Royal Statistical Society: Series B, 15, 253-261.
187. Yu, J.-W., Tian, G.-L., Tang, M.-L. (2008). Two new models for survey sampling with sensitive characteristic: design and analysis. Metrika, 67, 251-263.
188. Warner, S. L. (1965). Randomized response: a survey technique for eliminating evasive answer bias. Journal of the American Statistical Association, 60, 63-69.
189. Xie, H., Kulik, L., Tanin, E. (2011). Privacy-aware collection of aggregate spatial data. Journal of Data and Knowledge Engineering, 70, 576-595.
190. Bockenholt, U., Barlas, S., Van Der Heijden, P. G. M. (2009). Do randomized response designs eliminate response biases? An empirical study of non compliance behavior. Journal of Applied Economics, 24, 377-392.
191. Boeije, H., & Lensvelt-Mulders, G. (2002). Honest by chance: a qualitative interview study to clarify respondents' (non-) compliance with computer assisted randomized response. Bulletin Methodologie Sociologique, 75, 24-39.
192. Bose, M. (2013). Respondent privacy and estimation efficiency in randomized response surveys for disctrete-valued sensitive variables. arXiv:1303.5172v1.
193. Chaudhuri, A., Christofides, T. C., Saha, A. (2009). Protection of privacy in efficient application of randomized response techniques. Statistical Methods and Applications, 18, 389-418.
194. Chaudhuri, A., & Saha, A. (2004). Utilizing covariates by logistic regression modeling in improved estimation of population proportions bearing stigmatizing features through randomized responses in complex surveys. Journal of the Indian Society of Agricultural Statistics, 58, 190-211.
195. Christofides, T. C. (2003). A generalized randomized response technique. Metrika, 57, 195-200.
196. Christofides, T. C. (2010). Comments on a method of comparison of randomized response techniques. Journal of Statistical Planning and Inference, 140, 574-575.
197. Couper, M. P., Singer, E., Conrad, F. G., Groves, R. M. (2008). Risk of disclosure, perceptions of risk, and concerns about privacy and confidentiality as factors in survey participation. Journal of Official Statistics, 24, 255-275.
198. Coutts, E., & Jann, B. (2011). Sensitive questions in online surveys: experimental results for the randomized response technique (RRT) and the unmatched count technique (UCT). Sociological Methods & Research, 40, 169-193.
199. Greenberg, B. G., Abul-Ela, A.-L. A., Simmons, W. R., Horvitz, D. G. (1969). The unrelated question RR model: theoretical framework. Journal of the American Statistical Association, 64, 520-539.
200. Guerriero, M., & Sandri, M. F. (2007). A note on the comparison of some randomized response procedures. Journal of Statistical Planning and Inference, 137, 2184-2190.
201. Hong, Z., Yan, Z., Wei, L. (2010). A note of proposed privacy measures in randomized response models. Advances in Intelligent and Soft Computing, 77, 635-642.
202. Hubbard, M. L., Casper, R. A., Lessler, J. T. (1989). Respondent reactions to item count lists and randomized response. In Proceedings of the Survey Research Section of the American Statistical Association, ASA, 544-548.
203. Krebs, C. P., Lindquist, C. H., Warner, T. D., Fisher, B. S., Martin, S. L., Childers, J. M. (2011). Comparing sexual assault prevalence estimates obtained with direct and indirect questioning techniques. Violence Against Women, 17, 219-235.
204. Kuk, A. Y. C. (1990). Asking sensitive questions indirectly. Biometrika, 77, 436-438.
205. Lanke, J. (1976). On the degree of protection in randomized interviews. International Statistical Review, 44, 197-203.
206. Lensvelt-Mulders, G. J. L. M., Hox, J. J., Van Der Heijden, P. G. M. (2005). How to improve the efficiency of randomized response designs. Quality and Quantity, 39, 253-265.
207. 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.
208. Ljungqvist, L. (1993). A unified approach to measures of privacy in randomized response models: a utilitarian perspective. Journal of the American Statistical Association, 88, 97-103.
209. Mangat, N. S. (1992). Two stage randomized response sampling procedure using unrelated question. Journal of the Indian Society of Agricultural Statistics, 44, 82-87.
210. Mangat, N. S., Singh, S., Singh, R. (1993). On the use of modified randomization device in randomized response inquires. Metron, 51, 211-216.
211. Mangat, N. S., Singh, R. (1990). An alternative randomized response procedure. Biometrika, 77, 439-442.
212. Nathan, G., Sirken, M. G. (1988). Cognitive aspects of randomized response. In Proceedings of the Survey Research Section of the American Statistical Association (pp. 173-178). Washington DC: American Statistical Association.
213. Nayak, T. K. (1994). On randomized response surveys for estimating a proportion. Communications in Statistics-Theory and Methods, 23, 3303-3321.
214. Nayak, T. K., & Adeshiyan, S. A. (2009). A unified framework for analysis and comparison of randomized response surveys of binary characteristics. Journal of Statistical Planning and Inference, 139, 2757-2766.
215. Quatember, A. (2009). A standardization of randomized response strategies. Survey Methodology, 35, 143-152.
216. Quatember, A. (2012). An extension of the standardized randomized response technique to a multistage setup. Statistical Methods and Applications, 21, 475-484.
217. Singer, E. (2003). Exploring the meaning of consent: participation in research and beliefs about risks and benefits. Journal of Official Statistics, 19, 273-285.
218. Singh, R., Singh, S., Mangat, N. S., Tracy, D. S. (1995). An improved two stage randomized response strategy. Statistical Papers, 36, 265-271.
219. Tsuchiya, T., & Hirai, Y. (2010). Elaborate item count questioning: why do people underreport in item count responses? Survey Research Methods, 4, 139-149.
220. Van Der Heijden, P. G. M., Van Gils, G., Bouts, J., Hox, J. (2000). A comparison of randomized response, Computer assisted Self Interview, and Face to Face Direct Questioning; eliciting sensitive information in the context of welfare and unemployment benefit. Sociological Methods and Research, 28, 505-537.
221. Warner, S. L. (1965). Randomized response: a survey technique for eliminating evasive answer bias. Journal of the American Statistical Association, 60, 63-69.