English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 109955/140896 (78%)
Visitors : 46189753      Online Users : 1061
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 140.119/33897
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/33897


    Title: Cluster Analysis of Cancer Mortality in Taiwan Area
    Authors: 陳楓玲
    CHIN FOONG LING
    Contributors: 余清祥
    Yue Ching-Syang Jack
    陳楓玲
    CHIN FOONG LING
    Keywords: cluster
    rare disease
    case event data
    aggregate data
    cancer mortality
    Date: 2002
    Issue Date: 2009-09-17 18:45:21 (UTC+8)
    Abstract: 近年來,許多專家學者廣泛探討偵測稀有疾病的發生率或稱為叢集上的空間或空間對時間的統計方法及模型。這些方法大部分都是處理個別資料或是只能偵測接近圓形的叢集。在這篇論文中,根據Choynowski在1959年所探討的方法,我們進一步提出針對整體資料去偵測非圓形叢集的方法,並且會將此方法與Nagarwalla’s Spatial Scan Statistic做比較。同時,我們會呈現模擬結果中的型一、型二誤差來衡量此方法的可行性。另外,我們也會將此方法實際應用到台灣的癌症死亡資料做探討。
    In recent years, many statistical methods have been proposed for detecting excesses of rare diseases, i.e., clusters, in space or in space-time. Most of these methods deal with case-event or individual-level data and can only detect clusters with shape close to circles. In this study, adapting Choynowski`s (1959) idea, a simulation-based approach is proposed to detect non-circular clusters with aggregate or group-level data. The proposed cluster detection method will be used to compare with a frequently used method: Nagarwalla’s Spatial Scan Statistic. Computer simulation is used to illustrate the validity, with respect to Type-I and Type-II errors, of the proposed approach. In addition, the cancer mortality data in Taiwan area are also used as a demonstration of the proposed test.
    Reference: Bibliography
    Besag, J. and Newell, J. “The detection of clusters in rare diseases”, Journal of the Royal Statistical Society, Series A, 154, 143-155 (1991).
    Best, N. and Wakefield, J. “Accounting for inaccuracies in population counts and case registration in cancer mapping studies”, Journal of the Royal Statistical Society, Series A, 3, 363-382 (1999).
    Choynowski, M. “Maps based on probabilities”, Journal of the American Statistical Association, 54, 385-388 (1959).
    Cressie, N., “Statistics for spatial data (2nd ed.)”, Wiley-Interscience, New York, 1993.
    Cuevas, A., Febrero, M. and Fraiman, R., “Estimating the number of clusters”, The Canadian Journal of Statistics, 28, 367-382 (2000).
    Diggle, P.J., “Discussion on Cancer near nuclear installations”, Journal of the Royal Statistical Society, Series A, 152, 369-371 (1989).
    Diggle, P.J., “A point process modeling approach to raised incidence of a rare phenomenon in the vicinity of a prespecified point”, Journal of the Royal Statistical Society, Series A, 153, 349-362 (1991).
    Gardner, M.J., “Review of reported increases of childhood cancer rates in the vicinity of nuclear installations in the UK”, Journal of the Royal Statistical Society, Series A, 152, 307-325 (1989).
    Hills, M. and Alexander, F., “Statistical methods used in assessing the risk of disease near a source of possible environmental pollution: a review”, Journal of the Royal Statistical Society, Series A, 152, 353-363 (1989).
    Kulldorff, M. “A spatial scan statistic”, Communications in Statistics - Theory and Methods, 26, 1481-1496 (1997).
    Kulldorff, M. and Nagarwalla, N. “Spatial disease clusters: detection and inference”, Statistics in Medicine, 14, 799-810 (1995).
    Marshal, R. J. “A review of the statistical analysis of spatial patterns of disease”, Journal of the Royal Statistical Society, Series A, 154, 421-441(1991).
    Openshaw, S., Craft, A. W., Charlton, M. G. and Birch, J. M. “Investigation of leukaemia clusters by use of a geographical analysis machine”, Lancet, i, 272-273 (1988)
    Openshaw, S., Turner, A., Turton, I., Macgill, J., “Testing space-time and more complex hyperspace geographical analysis tool”, online at <http://www.ccg.leeds.ac.uk/smart/hyper.html>, 1988.
    Pickle, L. W., Mungiole, M., Jone, G. K. and White, A. A. “Exploring spatial patterns of mortality: the new atlas of United States mortality”, Statistics in Medicine, 18, 3211-3220 (1999).
    Rushton, G. and Lolonis, P. “Exploratory spatial analysis of birth defect rates in an urban population”, Statistics in Medicine, 15, 717-726 (1996).
    Sankoh, O. A., Heiko Becher, “Disease cluster methods in epidemiology and application to data on childhood mortality in rural Burkina Faso”, online at <http://www.hyg.uni-heidelberg.de/sfb544/publikationen.html>, 2002.
    Smith, G. H., “Disease cluster detection methods: the impact of choice of shape on the power of statistical tests”, online at <http://www.cobblestoneconcepts.com/ucgis2summer/smith/SMITH.HTM>, 2002.
    Stone, R. A. “Investigations of excess environmental risks around putative sources: statistical problems and a proposed test”, Statistics in Medicine, 7, 649-660 (1988).
    Tango, T. “A test for spatial disease clustering adjusted for multiple testing”, Statistics in Medicine, 19, 191-204 (2000).
    Turnbull, B. W., Iwano, E. J., Burnett, W. S., Howe, H. L. and Clark, L. C. “ Monitoring for clusters of disease: application to leukemia incidence in upstate New York”, American Journal of Epidemiology, 132, S136-143 (1990).
    Wartenberg, D. and Greenberg, M. “Detecting disease clusters: the importance of statistical power”, American Journal of Epidemiology, 132, S156-166 (1990).
    Whittemore, A. S., Friend, N., Brown, B. W. and Holly, E. A., “A test to detect clusters of disease”, Biometrika, 74, 631-635 (1987).
    Zhan, F. B. “Are deaths from liver cancer, kidney cancer, and leukemia clustered in San Antonio?”, Texas Medicine, 98, 51-55 (2002).
    Description: 碩士
    國立政治大學
    統計研究所
    90354017
    91
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0090354017
    Data Type: thesis
    Appears in Collections:[統計學系] 學位論文

    Files in This Item:

    File Description SizeFormat
    35401701.pdf48KbAdobe PDF21067View/Open
    35401702.pdf113KbAdobe PDF21197View/Open
    35401703.pdf129KbAdobe PDF21102View/Open
    35401704.pdf56KbAdobe PDF21120View/Open
    35401705.pdf99KbAdobe PDF21037View/Open
    35401706.pdf163KbAdobe PDF21204View/Open
    35401707.pdf146KbAdobe PDF21079View/Open
    35401708.pdf811KbAdobe PDF21141View/Open
    35401709.pdf176KbAdobe PDF21136View/Open
    35401710.pdf361KbAdobe PDF21114View/Open
    35401711.pdf135KbAdobe PDF21118View/Open
    35401712.pdf121KbAdobe PDF21122View/Open
    35401713.pdf1292KbAdobe PDF21199View/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