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Abstract Details
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Activity Number:
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185
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Type:
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Contributed
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Date/Time:
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Monday, July 30, 2012 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Survey Research Methods
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| Abstract - #305905 |
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Title:
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Bayesian Analysis of Randomized Response Models
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Author(s):
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Joon Jin Song*+ and Jong-Min Kim
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Companies:
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University of Arkansas and University of Minnesota-Morris
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Address:
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SCEN 301, Fayetteville, AR, 72701, United States
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Keywords:
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Randomized response ;
rare sensitive attribute ;
Sum score variable ;
Poisson regression model
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Abstract:
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Randomized response (RR) is an interview technique to sensitive questions that can protect respondent's privacy using a probability mechanism using randomization devices. Self-protection (SP) is introduced to evaluate the survey, describing the responses by participants who give the evasive answer without taking the result of the randomization device into account. In this study, we tackle two problems in RR using a Bayesian perspective: modeling RR sum score variables and estimation of the mean of the number of respondents who possessed a rare sensitive attribute.
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Authors who are presenting talks have a * after their name.
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