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Randomized Response Techniques for Complex Survey Designs
Author: LiMengZuo
Tutor: ZhuZhongYi
School: East China Normal University
Course: Probability Theory and Mathematical Statistics
Keywords: The randomization Q model Sensitive problems Stratified sampling Unequal Probability Sampling Two-sample model Single sample model
CLC: O212.2
Type: Master's thesis
Year: 2006
Downloads: 89
Quote: 0
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Abstract
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The survey sensitivity issues , respondents often refused to answer questions or provide false answer . In order to get the real answer of sensitive issues , in order to protect the privacy of the respondents , Warner in 1965 , the first proposed randomized Q sensitivity problem . He designed the model contains two sensitive question is completely contradictory . Technology research areas in the randomization Q decades , there have been a large number of the Warner model for the improved model , and some new methods of investigation . In order to further improve with the degree of the respondents in 1967 , Horvitz et al Improved Warner model . They suggested that the original inverse problem changed to a non-sensitive issues has nothing to do with the sensitivity characteristics . Since then , Moors (1971) and Horvitz model to make further improvements . In 2000 , Singh et al proposed two improved model of the Moors , the two models to make up for the defects of Moors of model destruction respondents privacy . However, the majority of the the Warner model for the improved model randomization Q \u0026 technology research areas are based on simple random sampling with replacement . In 2004 , Kim and Warde Warner (1965) model is applied to a stratified sample . In this article, we will be two models of Singh et al to be further extended to the stratified sampling and unequal probability sampling both complex sampling . On this basis , we give unbiased estimates of all models under the overall proportion of sensitive questions , the variance of the estimates , as well as other related properties .
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CLC: > Mathematical sciences and chemical > Mathematics > Probability Theory and Mathematical Statistics > Mathematical Statistics > Sampling theory,the frequency distribution
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