An improved randomized response model: estimation of mean

In this paper, we suggest a new randomized response model useful for collecting information on quantitative sensitive variables such as drug use and income. The resultant estimator has been found to be better than the usual additive randomized response model. An interesting feature of the proposed m...

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Bibliographic Details
Published inJournal of applied statistics Vol. 36; no. 12; pp. 1361 - 1367
Main Authors Gjestvang, Christopher R., Singh, Sarjinder
Format Journal Article
LanguageEnglish
Published Abingdon Taylor & Francis 01.12.2009
Taylor and Francis Journals
Taylor & Francis Ltd
SeriesJournal of Applied Statistics
Subjects
Estimates
Estimating techniques
estimation of mean
randomized response model
scrambling variables
sensitive variable
Statistical analysis
Online AccessGet full text
ISSN0266-4763
1360-0532
DOI10.1080/02664760802684151

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Summary:In this paper, we suggest a new randomized response model useful for collecting information on quantitative sensitive variables such as drug use and income. The resultant estimator has been found to be better than the usual additive randomized response model. An interesting feature of the proposed model is that it is free from the known parameters of the scrambling variable unlike the additive model due to Himmelfarb and Edgell [S. Himmelfarb and S.E. Edgell, Additive constant model: a randomized response technique for eliminating evasiveness to quantitative response questions, Psychol. Bull. 87(1980), 525-530]. Relative efficiency of the proposed model has also been studied with the corresponding competitors. At the end, an application of the proposed model has been discussed.
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ISSN:0266-4763
1360-0532
DOI:10.1080/02664760802684151