English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113822/144841 (79%)
Visitors : 51838484      Online Users : 169
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    政大機構典藏 > 商學院 > 統計學系 > 學位論文 >  Item 140.119/58662
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/58662


    Title: 貝氏方法應用於隨機化作答模式之研究
    A Bayesian Approach to Randomized Response Model
    Authors: 黃馨慧
    Contributors: 鄭天澤
    黃馨慧
    Keywords: 隨機化作答模式
    敏感性問題
    貝氏方法
    事前資訊
    Date: 2009
    Issue Date: 2013-07-01 17:00:43 (UTC+8)
    Abstract: 當作敏感性的議題調查時,如:性行為、未婚懷孕、墮胎…等若使用直接詢問(direct response)的方式,受訪者可能為顧及其隱私而拒絕回答或是不誠實作答,故在進行統計推論時恐有偏誤產生。為解決上述問題,Warner(1965)首先提出隨機化作答模式(randomized response model),而後有許多學者,如Greenberg等人(1969)、Mangot & Singh(1990)…等提出新的隨機化作答模式,以修正Warner的模式改善估計效率。然而Winkler & Franklin(1979)首先指出,「在隨機化的過程中會減少樣本所提供的資訊」,而結合事前資訊(prior information)貝氏估計法(Bayesian method)能彌補此缺點。其次,Pitz(1980)使用貝氏估計解決Fidler & Kleinknecht(1977)中的不合理估計值。第三,之後其他學者亦驗證在某些情況下,貝氏估計量的效率高於MLE。基於上述三個原因,本研究使用貝氏方法估計Huang(2004)隨機化作答模式的參數,結果證明能產生合理之貝氏估計值,且在某些情況下,其貝氏估計量的效率高於MLE。
    Reference: Abul-Ela, A. L. A., Greenberg, B. G., and Horvitz, D. G. (1967). “A Multi-Proportional Randomized Response Model,” Journal of the American Statistical Association, 62, 990-1008.
    Bar-Lev, S. K., Bobovich, E., and Boukai, B. (2003). “A Common Conjugate Prior Structure for Several Randomized Response Models,” TEST, 12, 101-113.
    Barabesi, L., & Marcheselli, M. (2006). “A Generalization of Huang’s Randomized Response Procedure for the Estimation of Population Proportion and Sensitivity Level.” Metron, vol. LXIV, n. 2, pp. 145-159.
    Chang, H. J., and Huang, K. C. (2001). “Estimation of Proportion and Sensitivity of a Qualitative Character,” Metrika, 53, 269-280.
    Chang, H. J., and Liang, D. H. (1996a). “A Two-Stage Unrelated Randomized Response Procedure for,” Australian journal of statistics, 38, 43-51.
    Chang, H. J., and Liang, D. H. (1996b). “A Randomized Response Procedure for Two-Unrelated Sensitive Questions,” Journal of Information & Optimization Sciences, 17, 185-198.
    Chaubey, Y.,and Li, W. (1995). “Comparison between Maximum Likelihood and Bayes Methods for Estimation of Binominal Probability with Sample Compositing,” Journal of Official Statistics, 11,379-390.
    Chaudhuri, A., Mukerjee, R. (1988). Randomized Response: Theory and Techniques. Marcel Dekker, New York.
    Christofides, T. C. (2003). “A Generalized Randomized Response Technique,” Metrika, 57, 195-200.
    Christofides, T. C. (2005). “Randomized Response in Stratified Sampling,” Journal of Statistical Planning and Inference, 128, 303-310.
    Fidler, D. S., and Kleinknecht, R. E. (1977). “Randomized Response Versus Direct Questioning: Two Data-Collection Methods for Sensitive Information,” Psychological Bulletin, 84, 1045-1049.
    Greenberg, B. G., Abul-Ela, A. L. A., Simmons, W. R., and Horvitz, D. G. (1969). “The Unrelated Question Randomized Response Model: Theoretical Framework,” Journal of American Statistical Association, 64, 520-539.
    Greenberg, B. G., Kuebler, R. R., Jr., Abernathy, J. R., and Horvitz, D. G. (1971). “Application of the Randomized Response Technique in Obtaining Quantitative Data,” Journal of American Statistical Association, 66, 243-250.
    Huang, K. C. (2004). “A Survey Technique for Estimating the Proportion and Sensitivity in a Dichotomous Finite Population,” Statistica Neerlandica, 58, 75-82.
    Kim, J. M., Tebbs J. M., and An S. W. (2006). “Extensions of Mangat’s Randomized Response Model,” Journal of Statistical Planning and Inference, 136, 1554-1567.
    Kim, J. M., and Warde, W. D. (2004). “A Stratified Warner’s Randomized Response Model,” Journal of Statistical Planning and Inference, 120, 155-165.
    Kuk, A. Y. C. (1990). “Asking Sensitive Questions Indirectly,” Biometrika, 77, 436-438.
    Mangat, N. S., and Singh, R. (1990). “An Alternative Randomized Response Procedure,” Biometrika, 77, 439-442.
    Mangat, N. S. (1994). “An Improved Randomized Response Strategy,” Journal of the Royal Statistical Society: Series B, 1, 93-95.
    Migon, H. S., and Tachibana, V. M. (1997). “Bayesian Approximations in Randomized Response Model,” Computational Statistics & Data Analysis, 24, 401-409.
    Pitz, G. F. (1980). “Bayesian Analysis of Random Response Models,” Psychological Bulletin, 87, 209-212.
    Singh, J. (1976). “Randomized Response a Method for Sensitive Surveys.” In Proceedings of the Social Statistics Section, p. 722. American Statistical Association.
    Winkler, R. L., and Franklin, L. A. (1979). “Warner’s Randomized Response Model: A Bayesian Approach,” Journal of the American Statistical Association, 74, 207-214.
    Warner, S. L. (1965). “Randomized Response : A Survey Technique for Estimating Evasive Answer Bias,” Journal of the American Statistical Association, 60, 63-69.

    王智立、蔡宛容,2007。應用一般化Greenberg無關聯隨機化作答模式於敏感問題之研究,中國統計學報,第45卷,頁189-205。
    Description: 碩士
    國立政治大學
    統計研究所
    96354003
    98
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0096354003
    Data Type: thesis
    Appears in Collections:[統計學系] 學位論文

    Files in This Item:

    File SizeFormat
    400301.pdf1053KbAdobe PDF2587View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback