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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/36924


    Title: 台灣地區基因檢測之意向及願付價格調查
    The Investigation of people`s intention and their willingness to pay toward genetic testing in Taiwan
    Authors: 王荷惠
    Wang, Ho Hui
    Contributors: 江振東
    王荷惠
    Wang, Ho Hui
    Keywords: 願付價格
    基因檢測
    加速失敗模型
    WTP
    Genetic testing
    AFT model
    Date: 2007
    Issue Date: 2009-09-18 20:10:13 (UTC+8)
    Abstract: 本研究的目的主要是想要探討台灣地區的人民對於基因檢測的意向及願付價格。資料來自於中央研究院所主導的一項電話訪問，其中有關願付價格的部分是透過條件評估法的方式來取得。針對願付價格的分析，我們藉由潛在變數模型將受訪者對於基因檢測的知識、態度和自我認知等資訊萃取出來，並視為新的解釋變數來進行分析。此外，僅完成單界詢價過程的受訪者的資訊也和提供完整回答的受訪者一併納入分析。
    結果顯示一個人的性別、教育程度、宗教信仰傾向及對基因檢測的態度會顯著影響是否願意免費參加基因檢測的意願。而在詢價過程中，一開始受訪者被問及的金額和此人其基因檢測相關的知識程度影響了他（她）是否願意付錢參加基因檢測。至於在願意付合理價格的人們之中，他們的健康程度、收入和自家人的癌症病史則皆為影響價格高低的因素。
    This study is aimed to explore people’s intention and their willingness to pay (WTP) for genetic testing in Taiwan. A telephone survey using contingent valuation method (CVM) was conducted by the Academia Sinica to collect the data. There are three unique features that distinguish our data analysis approach from the others. First, the covariates related to a respondent’s knowledge, attitude and perception (KAP) on genetic testing are generated through the use of a latent trait model. Second, the information collected from a respondent who completed only the single-bounded part of the survey is also included in the analysis. Third, reasons given by a respondent is used to decide whether he/she is willing to pay a lower price or unwilling to pay any price.
    It is shown that one’s gender, education level, religious tendency and attitude all have significant impact on whether a respondent is willing to try a free genetic test. When it comes to pay for it, the initial bid asked and the degrees of knowledge affect his/her decision a lot. For those who are willing to pay a reasonable price for genetic testing, their WTP depend largely on their health conditions, incomes, and cancer histories.
    Reference: 1. Barkat, A., Helali, J., Rahman, M., Majid, M. and Bose, M. L., (1995), “Knowledge, Attitude, Perception and Practices Relevant to the Utilization of Emergency Obstetric Care Services in Bangladesh: a Formative Study”, Dhaka: University Research Corporation, Bangladesh.
    2. Bartholomew, D. J. and Knott, M. (1999), Latent Variable Models and Factor Analysis. 2nd edition. London: Arnold.
    3. Bartholomew, D. J. and Leung, S. O. (2002), “A Goodness-of-Fit Test for Sparse 2p Contingency Tables”, British Journal of Mathematical and Statistical Psychology, 55: 1–15.
    4. Bartholomew, D. J., Steele, F., Moustaki, I. and Galbraith, J. I. (2002), The Analysis and Interpretation of Multivariate Data for Social Scientists. Boca Raton: Chapman & Hall.
    5. Carson, R. T., Hanemann, W. M. and Mitchell, R. C. (1986), “Determining the Demand for Public Goods by Simulating Referendums at Different Tax Prices”, Department of Economic working Paper, University of California, San Diego.
    6. Farewell, V. T. and Prentice, R. L. (1977), “A Study of Distributional Shape in Life Testing”, Technometrics, 19: 69-75.
    7. Hanemann, W. M. (1985), “Some Issues in Continuous- and Discrete-Response Contingent Valuation Studies”, Northeastern J. Agricultural Economics, 5–13.
    8. Hanemann, W. M., Loomis, J., and Kanninen, B. (1991), “Statistical Efficiency of Doubled-Bounded Dichotomous Choice Contingent Valuation”, American Journal of Agricultural Economics, 73: 1255-1263.
    9. Klein, J. P. and Moeschberger, M. L. (1997), Suvival Analysis: Techniques for Censored and Truncated Data, New York: Springer.
    10. Lawless, J. F. (2003), Statistical Models and Methods for Lifetime Data, 2nd edition. New Jersey: John Wiley.
    11. Moustaki, I. (2001), “GENLAT: A Computer Program for Fitting a One- or Two- Factor Latent Variable Model to Categorical, Metric and Mixed Observed Items with Missing Values”, Technical report, Statistics Department, London School of Economics and Political Science.
    12. Stewart, A. and Zimmern, R., (2003), “(Almost) Three Cheers for UK Genetics White Paper”, The Lancet, 362: 341–2.
    13. Tsai, I.-L., (2005), “A Three-Component Mixture Model in Willingness-to-Pay Analysis for General Interval Censored Data”, unpublished master`s thesis, National Chengchi University, Taiwan.
    14. Tsay, Yuh-Chyuan and Chen, Chen-Hsin (2008), “EHA (Event History Analysis)-Risk Free”, An unreleased website, Institute of Statistical Science, Academia Sinica, Taipei, Taiwan, ROC.
    15. Yamaguchi, K. (1992), “Accelerated Failure-Time Regression Models with a Regression Model of Surviving Fraction”, Journal of the American Statistical Association, 87: 284-292.
    Description: 碩士
    國立政治大學
    統計研究所
    95354012
    96
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0095354012
    Data Type: thesis
    Appears in Collections:[Department of Statistics] Theses

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