Abstract Details
Activity Number:
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138
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Type:
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Contributed
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Date/Time:
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Monday, August 5, 2013 : 8:30 AM to 10:20 AM
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Sponsor:
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Survey Research Methods Section
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Abstract - #309307 |
Title:
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Quasi-Empirical Bayes Estimates in Randomized Response Sampling
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Author(s):
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Oluseun Odumade*+ and Stephen Andrew Sedory and Sarjinder Singh
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Companies:
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Best Buy and Texas A&M University-Kingsville and Texas A&M University-Kingsville
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Keywords:
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Randomized response sampling ;
estimation of sensitive characteristics ;
Bayes estimation ;
Cramer-Rao lower bound of variance ;
Simulation study
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Abstract:
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In this paper, a notion of "quasi empirical" Bayes estimation is proposed for estimating the proportion of sensitive attribute in a population by making use of both a prior distribution of prevalence of the sensitive attribute in addition to the known prior distribution of an unrelated characteristic. The proposed quasi empirical Bayes estimates are compared with those of the unrelated question model due to Greenberg et al. (1969) by means of a simulation study. A quasi Cramer-Rao lower bound of variance is also suggested and compared to the variance of the Greenberg el al. (1969) estimator. Simulated situations are reported where the proposed lower bound of variance remains below the variance of the Greenberg et al (1969) estimator.
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Authors who are presenting talks have a * after their name.
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