淡江大學機構典藏:Item 987654321/74363
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    题名: 配對鑑取抽樣下疾病數量性狀之家族聚集性的檢測
    其它题名: Detecting familial aggregation of a quantitative trait with matched proband sampling
    作者: 許雅卿;Hsun, Ya-Ching
    贡献者: 淡江大學統計學系碩士班
    陳麗菁;Chen, Li-Ching
    关键词: 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;case-control family data;familial aggregation;generalized estimating equation;matched design;proband sampling;Quantile Regression;within-cluster resampling
    日期: 2011
    上传时间: 2011-12-28 18:24:52 (UTC+8)
    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。
    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.
    显示于类别:[統計學系暨研究所] 學位論文

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