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題名 廣義線性混合模式結合B-Spline在疾病地圖上之應用
Applying GLMM with B-Spline to Map Disease Rates
作者 連家斌
貢獻者 陳麗霞
連家斌
關鍵詞 GLMM
B-spline
CAR
日期 2004
上傳時間 2009-09-14
摘要 本論文探討了以廣義線性混合模式(GLMM)結合時間及空間效果的時間空間模式,以將地區特性、人口特徵等變數,及時間變數納入模式中。有關時間效果可用B-Spline方法建構固定或隨機的時間趨勢平滑函數,而空間效果則是將各地區的隨機效果以條件自我相關模式(CAR)描述。實證部份則是應用GLMM模式分析台灣本島350個鄉鎮市區自民國八十八年到九十一年的肝癌就診資料,依性別、年齡層加以整理,並將年齡層分為0~19歲、20~39歲、40 ~59歲、60歲以上,分別代表少、青、壯、老等四個年齡層;再採用GLMMGibbs結合R軟體各個資料集分別配適時間空間模式,估計各地區之相對風險並繪製疾病地圖,據以找出各年估計的相對風險高的地區。
參考文獻 中文部份:
1.賴景義:電腦輔助設計-B-spline基本特性介紹。
http://www.me.ncu.edu.tw/jylai/CAD/B-spline.doc
2.行政院衛生署--衛生統計資訊網。
http://www.doh.gov.tw/statistic/index.htm
3.財團法人預防醫學基金會-認識肝癌。
http://www.pmf.org.tw/hcc.htm
4. 蕭朱杏、莊愷瑋 (2001).地理統計於醫學與環境的應用,地理統計在農業和環境科學之應用研討會論文集,79-92頁,中國農業化學會。
5. 陳定信、賴明陽、陳健弘 (1991).本土醫學資料庫之建立及衛生政策上之應用,行政院衛生署八十年度委託研究計畫研究報告。
6. 行政院衛生署國民健康局 (2003).中華民國癌症死亡率分佈地圖集(1972-2001)。
7. 行政院衛生署國民健康局 (2003).中華民國癌症發生率分佈地圖集(1995-1998)。
英文部份:
1.Bernardinelli, L. and Montomoli, C. (1992). Empirical Bayes versus fully Bayesian analysis of geographical variation in disease risk. Statistics in Medicine. 11, 983-1007.
2.Besag, J., York, J. and Mollie, A. (1991). Bayesian image restoration, with two applications in spatial statistics. Annals of the Institute of Statistical Mathematics. 43, 1-21.
3.Breslow, N. E. and Clayton, D. G. (1993). Approximate inference in generalized linear mixed models. Journal of the American Statistical Association. 88, 421, 9-25.
4.Chambers, J. M. and Hastie, T. J. (1992). Chapter 7 of Statistical Models in S. Pacific Grove, Calif.:Wadsworth & Brooks/Cole Advanced Books & Software.
5.Clayton, D. and Kaldor, J. (1987). Empirical Bayes estimates of age-standardized relative risks for use in disease mapping. Biometrics , 43, 671-681.
6.De Boor, C. (1978). A Practical Guide to Splines. New York:Springer-Verlag.
7.Gelfand, A. E. and Smith, A.F.M. (1990). Sampling based approaches to calculating marginal desities. J. Am. Statist. Ass. 85, 389-409.
8.Gelfand, A. E., Hills, S. E., Racine-Poon, A. and Smith, A. F. M. (1990). Illustration of Bayesian inference in normal data models using Gibbs sampling. J. Am. Statist. Ass. 85, 972-985.
9.Lawson, A. B., Browne, W. J. and Vidal Roderiro, C. L. (2003). Disease Mapping with Winbugs and MLwin. England:John Wiley.
10.Myles, J. and Clayton, D. (2001). GLMMGibbs:An R package for estimating Bayesian Generalised Linear Mixed Models by Gibbs Sampling.
11.MacNab, Y. C. and Dean, C. B.(2000). Parametric bootstrap and penalized quasi-likelihood inference in conditional autoregressive models. Statistics in Medicine, 19, 2421-2435.
12.MacNab, Y. C. and Dean, C. B. (2001). Autoregressive spatial smoothing and temporal spline smoothing for mapping rates. Biometrics, 57, 949-956.
13.MacNab, Y. C. and Dean, C. B. (2002). Spatio-temporal modelling of rates for the construction of disease maps. Statistics in Medicine, 21, 347-358.
14.McCulloch, C. E. and Searle, S. R. (2001). Generalized, Liner, and Mixed models. New York:John Wiley.
15.Pickle, L. W. (2000). Exploring spatio-temporal patterns of mortality using mixed effects models. Statistics in Medicine, 19, 2251-2263.
16.Shene, C. K. (2003). Introduction to Computing with Geometry Notes.
http://www.cs.mtu.edu/~shene/COURSES/cs3621/NOTES/notes.html
17.Tsutakawa, R. K. (1988). Mixed model for analyzing geographical variability in mortality rates. J. Am. Statist. Ass., 83, 37-42.
18.Venables, W. N. and Ripley, B.D. (2002). Modern Applied Statistics with S. New York:Springer.
19.Walter, S. D. and Birnie, S. E. (1991). Mapping mortality and morbidity patterns: an international comparison. International Journal of Epidemiology .20 (3), 678-689.
描述 碩士
國立政治大學
統計研究所
92354010
93
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0923540101
資料類型 thesis
dc.contributor.advisor 陳麗霞zh_TW
dc.contributor.author (Authors) 連家斌zh_TW
dc.creator (作者) 連家斌zh_TW
dc.date (日期) 2004en_US
dc.date.accessioned 2009-09-14-
dc.date.available 2009-09-14-
dc.date.issued (上傳時間) 2009-09-14-
dc.identifier (Other Identifiers) G0923540101en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/30942-
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) 92354010zh_TW
dc.description (描述) 93zh_TW
dc.description.abstract (摘要) 本論文探討了以廣義線性混合模式(GLMM)結合時間及空間效果的時間空間模式,以將地區特性、人口特徵等變數,及時間變數納入模式中。有關時間效果可用B-Spline方法建構固定或隨機的時間趨勢平滑函數,而空間效果則是將各地區的隨機效果以條件自我相關模式(CAR)描述。實證部份則是應用GLMM模式分析台灣本島350個鄉鎮市區自民國八十八年到九十一年的肝癌就診資料,依性別、年齡層加以整理,並將年齡層分為0~19歲、20~39歲、40 ~59歲、60歲以上,分別代表少、青、壯、老等四個年齡層;再採用GLMMGibbs結合R軟體各個資料集分別配適時間空間模式,估計各地區之相對風險並繪製疾病地圖,據以找出各年估計的相對風險高的地區。zh_TW
dc.description.tableofcontents 第一章 緒論………………………………………………………1
     第一節 研究動機與目的 ……………………………………1
      第二節 研究架構 ……………………………………………2
     第二章 文獻探討 ………………………………………………3
     第一節 空間統計於醫學與環境的應用 ………………………3
      第二節 時間與空間模式 ………………………………………4
     第三節 台灣地區肝癌就診狀況之研究 ………………………5
     第三章 方法介紹 ………………………………………………7
      第一節 廣義線性混合模式介紹 ………………………………7
      第二節 CAR模式介紹 ………………………………………8
      第三節 B-spline之介紹 ………………………………………10
     3.3.1 B-spline節點 ………………………………………10
     3.3.2 B-spline基底函數 …………………………………11
     3.3.3 B-spline曲線的數學模式 …………………………12
      第四節 利用PQL估計GLMM參數 …………………………14
      第五節 利用Gibbs抽樣法估計GLMM參數 ………………15
     第四章 實證研究 ………………………………………………17
     第一節 資料概述與分析 ……………………………………20
      第二節 模式建立與應用 ……………………………………22
     第三節 模式估計與應用 ……………………………………26
     4.3. 適合度分析 ……………………………………29
     4.3.1女性0~19歲 ……………………………………32
     4.3.2女性20~39歲 ……………………………………35
     4.3.3女性40~59歲 ……………………………………38
     4.3.4女性60歲以上 ……………………………………41
     4.3.5男性0~19歲 ……………………………………44
     4.3.6男性20~39歲 ……………………………………47
     4.3.7男性40~59歲 ……………………………………49
     4.3.8男性60歲以上 ……………………………………52
     第四節 分析與探討 ……………………………………………54
     第五章 結論與建議 ……………………………………………61
     第一節 相對風險模式結論 ……………………………………61
      第二節 模式的改進方法 ………………………………………62
     參考文獻 …………………………………………………………64
     附錄1 各年度性別年齡層誤差分怖 …………………………67
     附錄2 肝癌各性別年齡層相對風險前10%的地區比較圖 ……72
     附錄3 相對風險模式收斂圖 ………………………………81
zh_TW
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0923540101en_US
dc.subject (關鍵詞) GLMMen_US
dc.subject (關鍵詞) B-splineen_US
dc.subject (關鍵詞) CARen_US
dc.title (題名) 廣義線性混合模式結合B-Spline在疾病地圖上之應用zh_TW
dc.title (題名) Applying GLMM with B-Spline to Map Disease Ratesen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) 中文部份:zh_TW
dc.relation.reference (參考文獻) 1.賴景義:電腦輔助設計-B-spline基本特性介紹。zh_TW
dc.relation.reference (參考文獻) http://www.me.ncu.edu.tw/jylai/CAD/B-spline.doczh_TW
dc.relation.reference (參考文獻) 2.行政院衛生署--衛生統計資訊網。zh_TW
dc.relation.reference (參考文獻) http://www.doh.gov.tw/statistic/index.htmzh_TW
dc.relation.reference (參考文獻) 3.財團法人預防醫學基金會-認識肝癌。zh_TW
dc.relation.reference (參考文獻) http://www.pmf.org.tw/hcc.htmzh_TW
dc.relation.reference (參考文獻) 4. 蕭朱杏、莊愷瑋 (2001).地理統計於醫學與環境的應用,地理統計在農業和環境科學之應用研討會論文集,79-92頁,中國農業化學會。zh_TW
dc.relation.reference (參考文獻) 5. 陳定信、賴明陽、陳健弘 (1991).本土醫學資料庫之建立及衛生政策上之應用,行政院衛生署八十年度委託研究計畫研究報告。zh_TW
dc.relation.reference (參考文獻) 6. 行政院衛生署國民健康局 (2003).中華民國癌症死亡率分佈地圖集(1972-2001)。zh_TW
dc.relation.reference (參考文獻) 7. 行政院衛生署國民健康局 (2003).中華民國癌症發生率分佈地圖集(1995-1998)。zh_TW
dc.relation.reference (參考文獻) 英文部份:zh_TW
dc.relation.reference (參考文獻) 1.Bernardinelli, L. and Montomoli, C. (1992). Empirical Bayes versus fully Bayesian analysis of geographical variation in disease risk. Statistics in Medicine. 11, 983-1007.zh_TW
dc.relation.reference (參考文獻) 2.Besag, J., York, J. and Mollie, A. (1991). Bayesian image restoration, with two applications in spatial statistics. Annals of the Institute of Statistical Mathematics. 43, 1-21.zh_TW
dc.relation.reference (參考文獻) 3.Breslow, N. E. and Clayton, D. G. (1993). Approximate inference in generalized linear mixed models. Journal of the American Statistical Association. 88, 421, 9-25.zh_TW
dc.relation.reference (參考文獻) 4.Chambers, J. M. and Hastie, T. J. (1992). Chapter 7 of Statistical Models in S. Pacific Grove, Calif.:Wadsworth & Brooks/Cole Advanced Books & Software.zh_TW
dc.relation.reference (參考文獻) 5.Clayton, D. and Kaldor, J. (1987). Empirical Bayes estimates of age-standardized relative risks for use in disease mapping. Biometrics , 43, 671-681.zh_TW
dc.relation.reference (參考文獻) 6.De Boor, C. (1978). A Practical Guide to Splines. New York:Springer-Verlag.zh_TW
dc.relation.reference (參考文獻) 7.Gelfand, A. E. and Smith, A.F.M. (1990). Sampling based approaches to calculating marginal desities. J. Am. Statist. Ass. 85, 389-409.zh_TW
dc.relation.reference (參考文獻) 8.Gelfand, A. E., Hills, S. E., Racine-Poon, A. and Smith, A. F. M. (1990). Illustration of Bayesian inference in normal data models using Gibbs sampling. J. Am. Statist. Ass. 85, 972-985.zh_TW
dc.relation.reference (參考文獻) 9.Lawson, A. B., Browne, W. J. and Vidal Roderiro, C. L. (2003). Disease Mapping with Winbugs and MLwin. England:John Wiley.zh_TW
dc.relation.reference (參考文獻) 10.Myles, J. and Clayton, D. (2001). GLMMGibbs:An R package for estimating Bayesian Generalised Linear Mixed Models by Gibbs Sampling.zh_TW
dc.relation.reference (參考文獻) 11.MacNab, Y. C. and Dean, C. B.(2000). Parametric bootstrap and penalized quasi-likelihood inference in conditional autoregressive models. Statistics in Medicine, 19, 2421-2435.zh_TW
dc.relation.reference (參考文獻) 12.MacNab, Y. C. and Dean, C. B. (2001). Autoregressive spatial smoothing and temporal spline smoothing for mapping rates. Biometrics, 57, 949-956.zh_TW
dc.relation.reference (參考文獻) 13.MacNab, Y. C. and Dean, C. B. (2002). Spatio-temporal modelling of rates for the construction of disease maps. Statistics in Medicine, 21, 347-358.zh_TW
dc.relation.reference (參考文獻) 14.McCulloch, C. E. and Searle, S. R. (2001). Generalized, Liner, and Mixed models. New York:John Wiley.zh_TW
dc.relation.reference (參考文獻) 15.Pickle, L. W. (2000). Exploring spatio-temporal patterns of mortality using mixed effects models. Statistics in Medicine, 19, 2251-2263.zh_TW
dc.relation.reference (參考文獻) 16.Shene, C. K. (2003). Introduction to Computing with Geometry Notes.zh_TW
dc.relation.reference (參考文獻) http://www.cs.mtu.edu/~shene/COURSES/cs3621/NOTES/notes.htmlzh_TW
dc.relation.reference (參考文獻) 17.Tsutakawa, R. K. (1988). Mixed model for analyzing geographical variability in mortality rates. J. Am. Statist. Ass., 83, 37-42.zh_TW
dc.relation.reference (參考文獻) 18.Venables, W. N. and Ripley, B.D. (2002). Modern Applied Statistics with S. New York:Springer.zh_TW
dc.relation.reference (參考文獻) 19.Walter, S. D. and Birnie, S. E. (1991). Mapping mortality and morbidity patterns: an international comparison. International Journal of Epidemiology .20 (3), 678-689.zh_TW