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系統識別號 U0002-2209201020512300
中文論文名稱 配對病例對照資料的條件羅吉斯迴歸分析
英文論文名稱 The conditional logistic regression analyses of matched case-control data
校院名稱 淡江大學
系所名稱(中) 統計學系碩士班
系所名稱(英) Department of Statistics
學年度 98
學期 2
出版年 99
研究生中文姓名 傅琪鈺
研究生英文姓名 Ci-Yu Fu
學號 697650108
學位類別 碩士
語文別 中文
口試日期 2010-06-25
論文頁數 47頁
口試委員 指導教授-陳麗菁
委員-陳蔓樺
委員-林哲揚
中文關鍵字 條件最大概似估計量  適合度檢定  羅吉斯迴歸模型  配對病例對照資料 
英文關鍵字 Conditional maximum likelihood estimator  Goodness-of-fit test  Logistic regression  Matched case-control data 
學科別分類 學科別自然科學統計
中文摘要 病例對照研究常被用來探索罕見疾病與潛在風險因子之間的關係。當干擾因子很難明確量化時,可採用配對設計控制干擾因子的影響,但是會伴隨過多特定配對層的截距. Breslow & Day (1980) 使用條件概似函數以解決干擾參數過多的問題。本文旨在介紹Chen & Wang (2010) 所提出的適合度檢定。該檢定統計量是由共變量二階動差的條件最大概似估計量和無母數最大概似估計量的差建構而來。最後,我們透過模擬研究與兩組實例分析評估該統計量在實務上的可行性。
英文摘要 Case-control studies are often used to explore the relationship between the rare disease and potential risk factors. When the confounding factors are difficult to be quantified, matching designs are used to control the confounding effects. But this results in highly stratum-specific intercepts. Breslow & Day (1980) adopt the conditional approach to eliminate the intercepts. In this paper, we introduce a new goodness-of-fit test which is proposed by Chen & Wang (2010). This test statistic is constructed by the difference between the estimates of the second moment of covariate which estimated by the conditional m.l.e. and nonparametric m.l.e., respectively. We assess the performance of the proposed method through simulation studies, and analyze two real datasets for illustration.
論文目次 目錄
第一章 緒論---------------------------------------------------------------------------1

第二章 羅吉斯迴歸模型的參數估計 ------------------------------------------6

第一節 條件羅吉斯迴歸模型 -----------------------------------------------6
第二節 條件最大概似估計量 ------------------------------------------------7

第三章 動差型式檢定統計量---------------------------------------------------11

第四章 模擬研究-------------------------------------------------------------------16

第五章 實例分析-------------------------------------------------------------------19

第一節 靜脈血栓性栓塞症配對病例對照研究-------------------------19
第二節 兒童急性骨髓白血病配對病例對照研究---------------------22

第六章 結論 ------------------------------------------------------------------------28

參考文獻--------------------------------------------------------------------------------30

附錄一: 靜脈血栓性栓塞症配對病例對照資料----------------------------33

附錄二: 兒童急性骨髓白血病配對病例對照資料------------------------41

表目錄
表1: 檢定統計量的型一誤差比率與檢定力-----------------------------18
表2: 靜脈血栓性栓塞症的變數名稱與記錄方式--------------------------21
表3: 以HRT和BMI為風險因子的條件羅吉斯迴歸分析---------------21
表4: 僅用BMI為風險因子的條件羅吉斯迴歸分析----------------------21
表5: 僅用HRT為風險因子的條件羅吉斯迴歸分析----------------------22
表6: 兒童急性骨髓白血病的變數名稱與記錄方式-----------------------25
表7: 向後選取法之篩選風險因子過程---------------------------------------25
表8: 所有風險因子之條件羅吉斯迴歸模型參數估計-------------------26
表9: 第一次篩選風險因子後之條件羅吉斯迴歸模型參數估計------26
表10: 第二次篩選風險因子後之條件羅吉斯迴歸模型參數估計-----26
表11: 第三次篩選風險因子後之條件羅吉斯迴歸模型參數估計-----27
表12: 第四次篩選風險因子後之條件羅吉斯迴歸模型參數估計-----27
表13: 第五次篩選風險因子後之條件羅吉斯迴歸模型參數估計-----27
表14: 第六次篩選風險因子後之條件羅吉斯迴歸模型參數估計----27
表15: 第七次篩選風險因子後之條件羅吉斯迴歸模型參數估計----27


參考文獻 參考文獻
[1] Agresti, A. (2002). Categorical Data Analysis, 2nd ed. New York: John Wiley.
[2] Arbogast, P. G. and Lin, D. Y. (2005). Goodness-of-fit methods for matched case-control studies. The Canadian Journal of Statistics, 32, 373-386.
[3] Breslow, N. E. and Day, N. E. (1980). Statistical Method in Cancer Research, 1, The Analysis of Case-Control Studies. Lyon: International Agency for Research on Cancer.
[4] Breslow, N. E. (1996). Statistics in epidemiology: The case-control study. Journal of the American Statistical Association, 91, 14-28.
[5] Cheng, K. F. and Chen, L. C. (2004). Testing goodness-of-fit of a logistic regression model with case-control data. Journal of Statistical Planning and Inference, 124, 409-422.
[6] Chen, L. C. and Wang, J. Y. (2010). Goodness-of-fit tests of the conditional logistic model for matched case-control studies. Working paper.
[7] Cox, D. R. (1970). The Analysis of Binary Data. London: Methuen.
[8] Daly, E., Vessey, M. P., Hawkins, M. M., Carrson, J. L., Gough, P. and Marsh, S. (1996). Risk of venous thromboembolism in users of hormone replacement therapy. The Lancet, 348, 977-980.
[9] Faraway, J. J. (2006). Extending the Linear Model With R: Generalized Linear, Mixed Effects and Nonparametric Regression Models. London: Chapman & Hall/CRC.
[10] Hosmer, D. W. and Lemeshow, S. (2000). Applied Logistic Regression, 2nd ed. New York: John Wiley.
[11] Kupper, L. L., Karon, J. M., Kleinbaum, D. G., Morgenstern, H. and Lewis, D. K. (1981). Matching in epidemiologic studies: validity and efficiency considerations. Biometrics, 37, 271-291.
[12] Le, C. T. (1998). Applied Categorical Data Analysis. New York: John Wiley.
[13] Prentice, R. L. and Pyke, R. (1979). Logistic disease incidence models and case-control studies. Biometrika, 66, 403-411.
[14] Qin, J. and Zhang, B. (1997). A goodness-of-fit test for logistic regression models based on case-control data. Biometrika, 84, 609-618.
[15] Thomas, D. C. and Greenland, S. (1983). The relative efficiencies of matched and independent sample designs for case-control studies. Journal of Chronic Diseases, 36, 685-697.
[16] Thompson, W. D., Kelse, J. L. and Walter, S. D. (1982). Cost and efficiency in the choice of matched and unmatched case-control study designs. American Journal of Epidemiology, 116, 840-851.
[17] Ury, H. K. (1975). Efficiency of case-control studies with multiple controls per case: continuous or dichotomous data. Biometrika, 31, 643-649.
[18] Woodward, M. (2005). Epidemiology: Study Design and Data Analysis, 2nd ed. London: Chapman & Hall/CRC.
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