系統識別號 | U0002-1308201110222700 |
---|---|
DOI | 10.6846/TKU.2011.00417 |
論文名稱(中文) | 配對鑑取抽樣下疾病數量性狀之家族聚集性的檢測 |
論文名稱(英文) | Detecting familial aggregation of a quantitative trait with matched proband sampling |
第三語言論文名稱 | |
校院名稱 | 淡江大學 |
系所名稱(中文) | 統計學系碩士班 |
系所名稱(英文) | Department of Statistics |
外國學位學校名稱 | |
外國學位學院名稱 | |
外國學位研究所名稱 | |
學年度 | 99 |
學期 | 2 |
出版年 | 100 |
研究生(中文) | 許雅卿 |
研究生(英文) | Ya-Ching Hsun |
學號 | 698650040 |
學位類別 | 碩士 |
語言別 | 繁體中文 |
第二語言別 | |
口試日期 | 2011-06-16 |
論文頁數 | 46頁 |
口試委員 |
指導教授
-
陳麗菁
委員 - 王俊毅 委員 - 鄧文舜 |
關鍵字(中) |
病例對照家庭資料 家族聚集性 廣義估計方程式 配對設計 鑑取抽樣 分量迴歸 群內重抽樣 |
關鍵字(英) |
case-control family data familial aggregation generalized estimating equation matched design proband sampling quantile regression within-cluster resampling |
第三語言關鍵字 | |
學科別分類 | |
中文摘要 |
檢測疾病是否存在家族聚集性(familial aggregation) 通常是遺傳流行病學的首要工作。在家族聚集性研究中,病例對照家庭設計 (case-control family design) 是典型的抽樣方式,此種抽樣方式是先取得病例和對照首被鑑取者 (case and control proband),然後招募該家族其他成員進入研究中。當有些主要的干擾變數難以衡量時,則採用配對病例對照家庭設計。雖然關於二元性狀或是未配對之家庭資料的分析文獻上被廣泛討論,然而針對病例對照家庭設計下數量性狀的分析卻少有討論。本文討論應用Liang & Pulver (1996) 所提出的廣義估計方程式方法,以及Wang & Zhao (2008) 所提出的加權分量迴歸分析,探討疾病的家族聚集性。我們亦應用 Hoffman et al. (2001) 所提出的群內重抽樣方法,分別配適線性迴歸模型以及分量迴歸模型以評估家族聚集性。本文將透過模擬研究比較這些方法實際執行的性質,並進行實例分析。 |
英文摘要 |
The preliminary work in genetic epidemiology is to determine whether a given disease shows familial aggregation. A typical design used for determination of familial aggregation should be the case-control family design which a case or a control proband is ascertained first, with subsequent recruitment of other members in the family. When some major confounders are difficult to measure, the matched case-control family is adopted. Although methods for analyzing familial data with a binary trait or unmatched design are well discussed, methods proposed for analysis of a quantitative trait with matched case-control family design get less attention. In this study, we apply the generalized estimating equation method (Liang & Pulver, 1996) and the weighted quantile regression analysis for clustered data (Wang & Zhao, 2008) to detect familial aggregation. We also apply the within-cluster resampling method of Hoffman et al., (2001) to fit linear regression model or quantile regression model to assess the familial aggregation. We assess the performance of the proposed methods through simulation studies and analysis of one dataset. |
第三語言摘要 | |
論文目次 |
目錄 第一章 前言..........................................1 第二章 以迴歸模式評估家族聚集性......................6 第一節 廣義估計方程式方法.........................6 第二節 加權分量迴歸方法...........................8 第三章 以重抽樣法評估家族聚集性.....................13 第一節 由原資料集重抽............................13 第二節 由虛擬家庭資料重抽........................16 第四章 模擬研究.....................................19 第五章 虛擬實例分析.................................24 第六章 結論.........................................28 參考文獻.............................................30 附錄 虛擬資料.......................................33 表目錄 1常態反應變數下, 的配對設計,群內重抽樣方法以及廣義估計方程式方法之經驗型I誤差與經驗檢定力......................23 2廣義估計方程式方法以及由虛擬家庭資料重抽樣方法之家族聚集性係數 的分析結果......................................27 |
參考文獻 |
參考文獻 英文部分: 1.Agresti, A. (2002). Categoridal Data Analysis,2nd.New York:John Wiley. 2.Anton, H. (2002). Elementary linear algebra,9nd.New York:John Wiley. 3.Breslow, N.E. (1996).Statistics in Epidemiology:The Case-Control Study. Journal of the American Statistical Association, 91, 14-28. 4.Chiu YH, Lin WY, Wang PE, Chen YD, Wang TT, Warwick J, Chen THH (2007). Population-based family case-control proband study on familial aggregation of metabolic syndrome: finding from Taiwanese people involved in Keelung Community-based Integrated Screening (KCIS No 5). Diabetes Res Clin Pract 75, 348-356. 5.Data,S. and Satten, G.A. (2005). Rank-sum tests for clustered data. Journal of the American Statistical Association 471, 908-915. 6.Hoffman E.B., Sen P.K., and Weinberg C.R. (2001). Within-cluster resampling. Biometrika, 88, 1121–1134. 7.Jung S.H., and Ying Z. (2003). Rank-based regression with repeated measurements data. Biometrika, 90, 732-740. 8.Koenker R.W., and Bassett G.W. (1978). Regression quantiles. Econometrica, 46, 33-50. 9.Koenker R.W., (2005). Quantile Regression. Cambridge : Cambridge University Press. 10.Liang, K.Y., and Beaty, T.H. (2000). Statistical designs for familial aggregation. Statistical Methods in Medical Research, 9, 543-562. 11.Liang, K.Y., and Pulver, A.E. (1996). Analysis of case-control/family sampling design. Genetic Epidemiology, 13, 253-270. 12.Liang, K.Y., Beaty, T.H., and Cohen B.H. (1986). Application of odds ratio regression models for assessing familial aggregation from case-control studies. American journal of Epidemiology, 124, 678-683. 13.Susser E., Susser M. (1989). Familial aggregation studies. American journal of Epidemiology, 129, 23-30. 14.Wang, M., Williamson, J.M., and Redline, S. (2004). A Semiparametric method for analyzing matched case-control family studies with a continuous outcome and proband sampling. Biometrics, 60, 644-650. 15.Wang Y. G., and Zhao Y. (2008). Weighted rank regression for clustered data analysis. Biometrics, 64, 39-45. 16.Williamson, J. M., Datta, S., and Satten, G. A. (2003). Marginal analyses of clustered data when cluster size is informative. Biometrics, 59, 36-42. 17.Williamson J., Tosteson T., Redline S., Liu X., and Dawson D. (1996). Familial aggregation studies with matched proband sampling. Humam Heredity, 46, 76-84. 中文部分: 1.林蕙敏,(2007),配對病例對照鑑取抽樣下家族聚集性的研究,淡江大學碩士論文。 2.戴政,(2002),遺傳流行病學:基因定位之遺傳設計與分析方法,第一版,藝軒圖書出版社。 |
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