NDLI: Estimation of population proportion in randomized response sampling using weighted confidence interval construction

Content Provider	Springer Nature Link
Author	Chang, Horng Jinh Kuo, Mei Pei
Copyright Year	2011
Abstract	This paper considers the problem of estimation for binomial proportions of sensitive attributes in the population of interest. Randomized response techniques are suggested for protecting the privacy of respondents and reducing the response bias while eliciting information on sensitive attributes. By applying the Wilson (J Am Stat Assoc 22:209–212, 1927) score approach for constructing confidence intervals, various probable point estimators and confidence interval estimators are suggested for the common structures of randomized response procedures. In addition, efficiency comparisons are carried out to study the performances of the proposed estimators for both the cases of direct response surveys and randomized response surveys. Circumstances under which each proposed estimators is better are also identified.
Starting Page	655
Ending Page	672
Page Count	18
File Format	PDF
ISSN	00261335
Journal	Metrika
Volume Number	75
Issue Number	5
e-ISSN	1435926X
Language	English
Publisher	Springer-Verlag
Publisher Date	2011-02-11
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Coverage probability Direct response Estimation efficiency Privacy protection Economic Theory Probability Theory and Stochastic Processes Statistics for Business/Economics/Mathematical Finance/Insurance Statistics
Content Type	Text
Resource Type	Article
Subject	Statistics and Probability Statistics, Probability and Uncertainty

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A stratified unrelated question randomized response model

Estimation of a sensitive proportion by Warner’s randomized response data through inverse sampling

A two-stage stratified Warner’s randomized response model using optimal allocation

Estimation of population proportion in randomized response sampling using weighted confidence interval construction

Bayesian estimation of proportion and sensitivity level in randomized response procedures

Protection of privacy in efficient application of randomized response techniques

Quantile interval estimation in finite population using a multivariate ratio estimator

A randomized response procedure for multiple-sensitive questions

Asymptotic infimum coverage probability for interval estimation of proportions

Estimation of population proportion in randomized response sampling using weighted confidence interval construction

Similar Documents

A stratified unrelated question randomized response model

Estimation of a sensitive proportion by Warner’s randomized response data through inverse sampling

A two-stage stratified Warner’s randomized response model using optimal allocation

Estimation of population proportion in randomized response sampling using weighted confidence interval construction

Bayesian estimation of proportion and sensitivity level in randomized response procedures

Protection of privacy in efficient application of randomized response techniques

Quantile interval estimation in finite population using a multivariate ratio estimator

A randomized response procedure for multiple-sensitive questions

Asymptotic infimum coverage probability for interval estimation of proportions

Estimation of population proportion in randomized response sampling using weighted confidence interval construction