學術產出-Theses

題名 Cluster Analysis of Cancer Mortality in Taiwan Area
作者 陳楓玲
CHIN FOONG LING
貢獻者 余清祥
Yue Ching-Syang Jack
陳楓玲
CHIN FOONG LING
關鍵詞 cluster
rare disease
case event data
aggregate data
cancer mortality
日期 2002
上傳時間 17-Sep-2009 18:45:21 (UTC+8)
摘要 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.
參考文獻 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).
描述 碩士
國立政治大學
統計研究所
90354017
91
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0090354017
資料類型 thesis
dc.contributor.advisor 余清祥zh_TW
dc.contributor.advisor Yue Ching-Syang Jacken_US
dc.contributor.author (Authors) 陳楓玲zh_TW
dc.contributor.author (Authors) CHIN FOONG LINGen_US
dc.creator (作者) 陳楓玲zh_TW
dc.creator (作者) CHIN FOONG LINGen_US
dc.date (日期) 2002en_US
dc.date.accessioned 17-Sep-2009 18:45:21 (UTC+8)-
dc.date.available 17-Sep-2009 18:45:21 (UTC+8)-
dc.date.issued (上傳時間) 17-Sep-2009 18:45:21 (UTC+8)-
dc.identifier (Other Identifiers) G0090354017en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/33897-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 統計研究所zh_TW
dc.description (描述) 90354017zh_TW
dc.description (描述) 91zh_TW
dc.description.abstract (摘要) 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。zh_TW
dc.description.abstract (摘要) 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.en_US
dc.description.tableofcontents Abstract
1 Introduction........................................1
2 Review of Related Work..............................3
2.1 Basic Statistical Model.............................3
2.2 Tests of Clustering.................................5
2.2.1 Global Tests ..................................5
2.2.2 Local Tests...................................6
2.2.3 Focused Tests.................................7
2.3 Detection of Clusters...............................8
2.4 Discussion..........................................8
3 Proposed Method....................................10
3.1 Cluster Model......................................10
3.2 Test of Clustering.................................11
3.3 Detection of Cluster...............................12
4 Simulations........................................15
4.1 Introductions and Background.......................15
4.2 Procedures for Simulations.........................18
4.2.1 Simulations for Models with No Cluster......18
4.2.2 Simulations for Models with One Cluster.....19
4.3 Simulation Results .................................19
4.3.1 Simulations for Models with No Cluster......19
4.3.2 Simulations for Models with One Cluster– Specified Shapes............................22
4.3.3 Simulations for Models with One Cluster– Specified Locations.........................26
5 Comparison of Cluster Detection Methods on
Synthetic Data Sets................................29
6 Applications.......................................31
6.1 Test of clustering.................................31
6.2 Detection of cluster...............................33
6.3 Discussions........................................35
7 Conclusions and Future Work........................36
7.1 Conclusions........................................36
7.2 Future Work........................................38
Bibliography.......................................40
Appendix A Models in Simulations...................43
Appendix B Tables of SaTScan Results...............45
Appendix C Tables of Empirical Clustering Results..48
zh_TW
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dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0090354017en_US
dc.subject (關鍵詞) clusteren_US
dc.subject (關鍵詞) rare diseaseen_US
dc.subject (關鍵詞) case event dataen_US
dc.subject (關鍵詞) aggregate dataen_US
dc.subject (關鍵詞) cancer mortalityen_US
dc.title (題名) Cluster Analysis of Cancer Mortality in Taiwan Areazh_TW
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) Bibliographyzh_TW
dc.relation.reference (參考文獻) Besag, J. and Newell, J. “The detection of clusters in rare diseases”, Journal of the Royal Statistical Society, Series A, 154, 143-155 (1991).zh_TW
dc.relation.reference (參考文獻) 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).zh_TW
dc.relation.reference (參考文獻) Choynowski, M. “Maps based on probabilities”, Journal of the American Statistical Association, 54, 385-388 (1959).zh_TW
dc.relation.reference (參考文獻) Cressie, N., “Statistics for spatial data (2nd ed.)”, Wiley-Interscience, New York, 1993.zh_TW
dc.relation.reference (參考文獻) Cuevas, A., Febrero, M. and Fraiman, R., “Estimating the number of clusters”, The Canadian Journal of Statistics, 28, 367-382 (2000).zh_TW
dc.relation.reference (參考文獻) Diggle, P.J., “Discussion on Cancer near nuclear installations”, Journal of the Royal Statistical Society, Series A, 152, 369-371 (1989).zh_TW
dc.relation.reference (參考文獻) 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).zh_TW
dc.relation.reference (參考文獻) 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).zh_TW
dc.relation.reference (參考文獻) 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).zh_TW
dc.relation.reference (參考文獻) Kulldorff, M. “A spatial scan statistic”, Communications in Statistics - Theory and Methods, 26, 1481-1496 (1997).zh_TW
dc.relation.reference (參考文獻) Kulldorff, M. and Nagarwalla, N. “Spatial disease clusters: detection and inference”, Statistics in Medicine, 14, 799-810 (1995).zh_TW
dc.relation.reference (參考文獻) 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).zh_TW
dc.relation.reference (參考文獻) 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)zh_TW
dc.relation.reference (參考文獻) 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.zh_TW
dc.relation.reference (參考文獻) 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).zh_TW
dc.relation.reference (參考文獻) Rushton, G. and Lolonis, P. “Exploratory spatial analysis of birth defect rates in an urban population”, Statistics in Medicine, 15, 717-726 (1996).zh_TW
dc.relation.reference (參考文獻) 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.zh_TW
dc.relation.reference (參考文獻) 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.zh_TW
dc.relation.reference (參考文獻) Stone, R. A. “Investigations of excess environmental risks around putative sources: statistical problems and a proposed test”, Statistics in Medicine, 7, 649-660 (1988).zh_TW
dc.relation.reference (參考文獻) Tango, T. “A test for spatial disease clustering adjusted for multiple testing”, Statistics in Medicine, 19, 191-204 (2000).zh_TW
dc.relation.reference (參考文獻) 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).zh_TW
dc.relation.reference (參考文獻) Wartenberg, D. and Greenberg, M. “Detecting disease clusters: the importance of statistical power”, American Journal of Epidemiology, 132, S156-166 (1990).zh_TW
dc.relation.reference (參考文獻) Whittemore, A. S., Friend, N., Brown, B. W. and Holly, E. A., “A test to detect clusters of disease”, Biometrika, 74, 631-635 (1987).zh_TW
dc.relation.reference (參考文獻) Zhan, F. B. “Are deaths from liver cancer, kidney cancer, and leukemia clustered in San Antonio?”, Texas Medicine, 98, 51-55 (2002).zh_TW