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E-raamat: Randomized Response and Indirect Questioning Techniques in Surveys

(Indian Statistical Institute, Kolkata, India)
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"A long-standing problem in survey research is that respondents are often reluctant to give truthful answers to sensitive questions. The randomized response technique (RRT) addresses this problem by guaranteeing respondents' anonymity and minimizing their discomfort. The key to this is that respondents determines which question they answer using some probability device, such as a coin flip or a roll of the dice. In this book, one of the world's leading experts on the subject summarizes the current state of the theory and practice of RRT. He examines how to extend the theory to situations employing unequal probability sampling"--Provided by publisher.

"For surveys involving sensitive questions, randomized response techniques (RRTs) and other indirect questions are helpful in obtaining survey responses while maintaining the privacy of the respondents. Written by one of the leading experts in the world on RR, randomized Response and Indirect Questioning Techniques in Surveys describes the current state of RR as well as emerging developments in the field. The author also explains how to extend RR to situations employing unequal probability sampling.Whilethe theory of RR has grown phenomenally, the area has not kept pace in practice. Covering both theory and practice, the book first discusses replacing a direct response (DR) with an RR in a simple random sample with replacement (SRSWR). It then emphasizes how the application of RRTs in the estimation of attribute or quantitative features is valid for selecting respondents in a general manner. The author examines different ways to treat maximum likelihood estimation; covers optional RR devices, which provide alternatives to compulsory randomized response theory; and presents RR techniques that encompass quantitative variables, including those related to stigmatizing characteristics. He also gives his viewpoint on alternative RR techniques, including the item count technique, nominative technique, and three-card method"--Provided by publisher.

"For surveys involving sensitive questions, randomized response techniques (RRTs) and other indirect questions are helpful in obtaining survey responses while maintaining the privacy of the respondents. Written by one of the leading experts in the world on RR, randomized Response and Indirect Questioning Techniques in Surveys describes the current state of RR as well as emerging developments in the field. The author also explains how to extend RR to situations employing unequal probability sampling.Whilethe theory of RR has grown phenomenally, the area has not kept pace in practice. Covering both theory and practice, the book first discusses replacing a direct response (DR) with an RR in a simple random sample with replacement (SRSWR). It then emphasizes how the application of RRTs in the estimation of attribute or quantitative features is valid for selecting respondents in a general manner. The author examines different ways to treat maximum likelihood estimation; covers optional RR devices, which provide alternatives to compulsory randomized response theory; and presents RR techniques that encompass quantitative variables, including those related to stigmatizing characteristics. He also gives his viewpoint on alternative RR techniques, including the item count technique, nominative technique, and three-card method"--

Provided by publisher.

Arvustused

The book compiles the important mathematical contributions in the area of RR readers interested in a summary of the statistical advances on RR will certainly find this book to be a good resource. It is a well-written and edited book and I congratulate the author for his work. Mariano Ruiz Espejo, Biometrics, December 2012

Preface xiii
Acknowledgments xv
1 Why We Need One More Monograph on Randomized Response
1(8)
2 Warner's Randomized Response Technique
9(28)
Introduction
9(1)
Warner Model
9(1)
Simple Random Sampling with Replacement
10(1)
Chaudhuri and Pal's Estimators
11(8)
Chaudhuri, Bose, and Dihidar's Estimators
19(10)
Inverse SRSWR
29(8)
Chaudhuri, Bose, and Dihidar's Estimators
29(8)
3 Randomized Response Technique in General Sampling Design
37(28)
Introduction
37(3)
Warner's Model
40(1)
Unrelated Question Model
41(3)
Kuk's RRT
44(2)
Christofides's RRT
46(3)
Forced Response Scheme
49(2)
Mangat and Singh's RRT
51(1)
Mangat's Scheme
52(2)
Mangat, Singh, and Singh's Scheme
54(1)
Singh and Joarder's Scheme
55(1)
Dalenius and Vitale's Scheme
56(2)
Takahasi and Sakasegawa's Scheme Modified by Pal
58(3)
Liu, Chow, and Mosley's RRT
61(4)
4 Maximum Likelihood Approach
65(10)
Introduction
65(1)
Illustrations
66(9)
Warner's Model
66(3)
Mangat and Singh's Model
69(1)
Kuk's Model
70(1)
Unrelated Characteristics Model
71(4)
5 Optional RRT
75(8)
Introduction
75(1)
Illustrations
76(6)
Chaudhuri and Saha's ORR Technique
76(3)
Chaudhuri and Dihidar's ORR Technique
79(3)
Comments
82(1)
6 Protection of Privacy
83(8)
Introduction
83(1)
Illustrations
83(8)
7 Quantitative Characteristics
91(22)
Introduction
91(1)
Review of Literature
91(22)
8 Other Indirect Questioning Techniques
113(8)
Introduction
113(1)
Item Count Technique
114(2)
Nominative Technique
116(3)
Three-Cards Method
119(2)
9 Miscellaneous Techniques, Applications, and Conclusions
121(68)
Introduction
121(1)
Review
121(66)
Sinha and Hedayat
121(2)
R. Arnab
123(12)
Nayak, Nayak and Adeshiyan, Christofides, and Quatember
135(3)
Guerriero and Sandri
138(1)
Padmawar and Vijayan
138(2)
Works on RR by N.S. Mangat, Ravindra Singh, Sarjinder Singh, Sat Gupta, and Bhisham Gupta
140(22)
Sarjinder Singh, Stephen Horn, Ravindra Singh, and N.S. Mangat
162(1)
Sarjinder Singh, Stephen Horn, and Sadeq Chowdhury
163(1)
Chang and Liang
164(2)
Kajal Dihidar
166(1)
Chang, Wang, and Huang and Huang
167(3)
Kim and Elam and Kim and Warde
170(2)
Kim, Tebbs, and An, Chua and Tsui: Their Works
172(3)
Carlos N. Bouza
175(1)
Joe Kerkvliet
176(1)
N.J. Scheers
177(1)
Umesh and Peterson
177(1)
Chris Gjestvang and Sarjinder Singh
178(1)
Landsheer, Heijden, and Gils
178(1)
Heijden and Gils
178(1)
Heiden, Gils, Bouts, and Hox
179(1)
Tracy and Mangat
179(1)
Sanghamitra Pal
180(2)
Amitava Saha
182(1)
Strachan, King, and Sarjinder Singh
182(1)
Sanghamitra Pal
183(1)
Ardo van den Hout and P.G.M. van der Heijden
184(1)
D.E. Stem and R.K. Steinhorst
184(1)
Ravindra Singh, Sarjinder Singh, and N.S. Mangat
185(1)
D.R. Bellhouse
185(1)
Yan, Zaizai and Nie, Zankan
186(1)
Epilogue
187(2)
10 Illustrative Simulated Empirical Findings
189(6)
Warner's RR versus Unrelated Question Model-Based RR in Unequal Probability Sampling as against Equal Probability Sampling
189(4)
Simulated Illustration of a Numerical Study of "Protection of Privacy" in RR Surveys
193(1)
Concluding Remarks
193(2)
References 195(12)
Index 207
Arijit Chaudhuri is a professor in the Applied Statistics Unit at the Indian Statistical Institute. Dr. Chaudhuri has published nearly 90 research papers in a variety of journals. He is the co-author of Survey Sampling: Theory and Methods, Second Edition (CRC Press, March 2005). His research interests include survey sampling and reliability.